I see alot of comments talking about age, but let’s be real we clicked on this video because we wanted to learn. everyone’s life story is different, now get focused.
Hats off to this man. I'm 27, 28 this year and I try changing my life, attending university and trying to follow valuable courses shared by fCC. Happy new year to everyone, hopefully your dreams and goals will be materialized this year!
The kid's 15. My god, look at the teaching skills and confidence at such age while delivering one of the hardest courses. He is gonna reach great heights ✌️✌️
And then there is me, a 22 year old CS majors learning from a 15 year old master. This is a proof that age is just a number, hats off to this guy may he fulfill all his dreams
Either you focus on your education and career in your youth, or you focus on social life, hobbies/passion, rest/health or whatever makes you feel good ("living"). Either path you choose, you're going to have regrets when you're older because you didn't take the other path. This kid probably sacrifices things like social life, rest and other aspects of life that we focused on in our youth, which he might regret missing out on later in life just like we may regret not learning machine learning at 15. But it's really pointless to have regrets. You can still learn when you're older, or focus on what makes you happy.
4:56:00 Understanding decision trees is crucial for machine learning. 4:59:58 Recollection of high variance and high bias 5:02:08 Ensemble learning relies on the concept of majority vote. 5:06:30 Ensemble learning involves combining output from multiple models to improve accuracy. 5:08:32 Ensemble learning is widely used in industry and Kaggle competitions. 5:12:48 Bagging involves training models on subsets of the data and combining them for improved performance. 5:15:04 Sampling with Replacement in Supervised Learning 5:19:19 Bagging helps in reducing the variance 5:21:24 Bagging helps in reducing model variance. 5:25:38 Bagging technique helps in combining base models to reduce variance 5:27:41 Random forest is a combination of decision trees, bagging, and feature bagging. 5:31:52 Ensemble learning uses different models for higher accuracy 5:33:53 Using out of bag points for cross validation and model evaluation 5:38:09 Understanding Trivially Parallelized and Extremely Randomized Trees 5:40:20 Extremely randomized trees reduce variance using column sampling. 5:44:39 Using the Random Forest Classifier in scikit-learn 5:46:53 Explanation of various parameters in machine learning algorithm 5:51:08 RMSE is not default, you have to create your own function for it. 5:53:15 Boosting is a popular ensemble technique. 5:57:28 Bagging vs Boosting 5:59:35 Using boosting to reduce model bias. 6:03:32 Minimizing residual and fitting models for error reduction 6:05:32 Gradient boosting trains model to fit the residual from previous model 6:09:38 Gradient boosting is a powerful algorithm for improving error under training set. 6:11:50 Gradient boosting converts weak learners into strong learners. 6:15:46 Adaboost algorithm for machine learning 6:18:02 Training the model for boosting with residuals 6:22:28 Training data, loss function, and base learners in machine learning. 6:24:32 Regularization and shrinkage are used to address high bias and overfitting in boosting. 6:28:41 Implementation of Gradient Boosting Classifier 6:30:53 Adaptive boosting focuses on reducing overfitting with key hyperparameters 6:34:49 Learned about ada boost classifier 6:36:48 XGBoost is an advanced algorithm of gradient boosting 6:40:59 Regularization, construction algorithm, and parameter tuning in XGBoost 6:43:14 Introduction to Stacking in Ensemble Learning 6:47:44 Difference between bagging and stacking 6:49:54 Understanding bias and variance tradeoff in machine learning model tuning. 6:54:19 Ensemble Learning Techniques 6:56:32 Stacking is a method to train a second-level classifier on the predictions of base learners 7:00:47 Stacking classifier is better than random forest 7:02:50 Applying stacked classification using a grid search 7:06:51 Learned about ensemble learning 7:08:47 The course covers neural networks, GANs, and internships 7:12:50 Overview of unsupervised learning applications 7:14:48 Customer Segmentation for Personalized Recommendations 7:18:58 Unsupervised learning has applications in biology and business 7:20:53 Machine learning involves social network analysis and image segmentation with unsupervised learning 7:25:09 Outliers can be addressed using clustering algorithms like DBSCAN and isolation forest. 7:26:57 Introduction to clustering in machine learning 7:31:06 Segmenting data points into clusters 7:33:16 Optimizing intra and inter-cluster distances 7:37:40 Evaluation technique for clustering model 7:39:44 Understanding Cluster Evaluation Metrics 7:43:53 Introduction to clustering in machine learning 7:46:00 Exploring types of clustering 7:49:59 Hierarchical and Non-hierarchical clustering techniques. 7:52:06 Clustering is grouping similar objects with inter and intra-clusters. 7:56:08 Overview of k-means clustering with subtopics 7:58:24 Introduction to k-means clustering with 2 centroids 8:02:17 K-means clustering algorithm visualization 8:04:24 The K-means clustering algorithm involves cluster assignment and centroid re-calculation. 8:08:26 Understanding K-means clustering and distance calculation 8:10:21 Random initialization can cause clustering problems. 8:14:35 K-means clustering algorithm overview 8:16:33 K-means clustering limitations and time complexity 8:20:27 Introduction to Hierarchical Clustering 8:22:30 Clustering with example points P1, P2, P3, P4 8:26:38 Hierarchical clustering creates a hierarchy of clusters from individual data points. 8:28:40 Understanding divisive and agglomerative clustering 8:32:35 Understand the basic algorithm in agglomerative clustering 8:34:35 Approximating matrix approximation 8:38:39 Methods to measure similarity between clusters 8:40:46 The minimum approach finds the minimum distance and merges clusters accordingly 8:44:52 Explaining the process of merging clusters using distance comparison 8:46:48 Hierarchical clustering creates clusters by merging or splitting them based on distance 8:50:42 Build a heart failure prediction model 8:52:42 Building machine learning models for healthcare early detection and spam detection system. 8:56:34 Summary of data loading and basic exploration 8:58:32 Understanding business solutions through data analysis 9:02:23 Working with imbalanced data 9:04:27 Imbalance means that your data is not equally distributed between classes 9:08:33 Filtering and analyzing data in pandas 9:10:48 Observation about the number of cases and inference for age group 50+ 9:15:06 Correlation values indicate linear relationship strength. 9:17:01 Data set development involves dividing data into training and testing sets. 9:21:00 Increase max iterations for non-converging data 9:23:06 Stochastic gradient descent is used to minimize approximation in machine learning. 9:27:05 Model evaluation techniques and parameter tuning 9:29:02 Optimizing model performance with randomized search 9:32:52 The Next project is about the spam detector system 9:35:08 Text-to-number conversion for machine learning model 9:39:22 Text cleaning is essential for data preprocessing. 9:41:31 Text preprocessing techniques like stemming and lemmatization 9:45:55 Stemming reduces inflection into words. 9:47:57 Converting text data into a numerical matrix for training 9:52:20 Introduction to basic concepts of machine learning
As someone who is looking to break into this field, as an entrepreneur, and as a husband and a father, you are truly an inspiration. What you are doing is incredible and I wholeheartedly support you. Keep going. You are the future.
this is the perfect example of winning the genetic lottery... lmao... it has nothing to do with knowledge.... 🤣🤣🤣... No scientists have fully understood the brain yet.
@@ishananaguru exactly. Each person is different, and we can keep working on our ourselves to reach our potential, that upper limit will not be same between people and shouldn't be measured in the first place cuz there are a lot of variables which cannot be measured when it comes to the brain
I'm amazed at your intelligence and other Indian men! i once visited Delhi , a tired city full of tired people, but i was amazed by the intelligence and wisdom of the people! Thank you for your intelligence🙏
Don't get discouraged, he obviously has impressive abilities, which the average person doesn't. But even if you procrastinated throughout middle school, it's never late to start and catch up. Don't think about it, just start(JUST DO IT!!!)
I'd almost wish that but internet wasn't really a thing i could access more than 10m a day during phys class while the teacher wasn't looking around so... No, i'd just wished i hadn't gave up on everything 15y ago when i got access to the internet and free knowledge like that :/ Better late than never however.
Thank you so much for the video! very easy to follow. I graduated in a data science major but didn't learn it well back in the school. Your video picked up so much of my memories and helped me enhanced my ML knowledge. If there is a chance to go back to the collage, I won't waste my time on useless things and just focus on learning. Again, thank you for your effort on this video!
You've just saved my life bro. I really love ML but I was unable to understand the concepts of algorithms due to less interest in mathematical terms. but you are savior. You are teaching in really easy manner. For me on entire youtube u r the best teacher for ML. Just completed one hour of this video and going on.
I've just started ML (supervised) at the age of 21 after having a mathematical degree. I feel ashamed after watching this video but happy cuz this guy explains things better than my PhD teacher .
The whole course is so comprehensive , thank you! This 9+ hours of knowledge tsunami actually represents a higher quality of teaching than some university courses in the same topic :D
Just a questions, how is this course really? and is this for beginners, and if I am beginner what will be my level after completing this course. If I learn the content of this course well then will I qualified to join companies like MMAANG. (and ofcourse I know few other things as well)
@@ainovice6634 As the title of this video suggests this is a beginner's course, meaning that it gives you the fundamentals of machine learning. Landing a position at big companies (FAANG, MMAANG, or whatever acronym you use) requires specialized knowledge which could further require years of experience and a degree from a university or an educational institution. You can treat this course as the first step towards becoming a specialist in the field
I will be honest - I've first wanted to switch to another video just by lookig at how young the lecturer is. But I've decided to keep watching and I totally love the way the lecturer explains things.
Hats off to you.. Really impressing teaching and your knowledge... Many students don't know what to do with their career even after their graduation...
@Abhay Bisht CSDS Hi I already started in my channel, If you see ML002 ( It starts from teaching linear algebra, calculus, probability theory and stats ), Search for ML002 Newera, U will get that!
Wow, I usually have a difficult time understanding Indian English accent but you speak so clearly and well that I didn't have trouble understanding at all.
I just want to point out, while this course is amazing, and it's crazy how much this dude knows (I mean, he looks like 16 years old or something), there's quite a lot of inaccuracies in the equations and way he formulates problems. Makes me think he "memorised" the maths, rather than actually try to understand them.
Such a wonderful person. Who wishes to teach Machine Learning for us .He wish to do things like Ratan Tata.....U will reach More than that Mr Ayush......
In LInear Regression , the cost funtion is 1/m * (summation of square of difference between ground value and predicted value).But in the tutorial you wrote 1/m + (summation part). Change it. Other than that your video is awesome.
I appreciating free code camp, I have seen many videos, code camp always encouraging developing people, like a flask, NLP everywhere, thankyou so much, all are want this kind of help, you will develop too faster, that's the boon from my side.
This kid is freaking 15, just checked out his channel and damn. He already knows data structures and algo's, GANs and other complex ML algorithms not just by code but also conceptually with is what is harder to grasp.
This video helps me a lot to start machine learning. Hats off to this young man. BTW, Could we access to the lecture slids? That will be great helpful.
Note: At 50:20 the correct is (pred - act)^2 because if u calculate (pred - act) and sum for all x, the points above, and the points below will cancel each other, since (pred - act) < 0 if act > pred and (pred - act) > 0 if act < pred.
Thankyou for this course. I learned a lot. just a few suggestions: 1) Stop the accent. 2) Clearity of thought needs to improve. 3) Improve spoken english. with that being said, I appreciate your efforts and salute you for your expertise.
I have a little question, in the whole calculation of RMSE in linear regression , why are we addting 1/m instead of multiplying it by 1/m. Even if we consider the units of the entities, we are trying to add a number with distance .
Am also of same age as Ayush and this video is an eye opener for me that where I actually stand in coding community. I have to learn a lot....Btw, waiting for this video :)
You are lucky. You have time on your side! At 15, don't smoke. Don't drink. Party less. Don't play video games. Live, breathe, and sh.. Data Science/Mathematics/CS. You can do it. The world is your oyster!!
@@darkreaper4990 I agree 100%! I meant don't lose yourself in video games! I actually still play chess almost every day or my life. As a kid, I played on my Atari, nintendo, snes, playstation, etc. So, I support video games!
10h tutorial uploaded 5h ago, and yet people are thanking him for best course they ever had. I mean come on people... Did you watch it on 2x speed and made 0 notes or took no breaks at all? What's the viability of your comments. It rather sound like a fanboys trying to get their comments to the top ...
Hey, Don't take it in wrong way, Plz read the comments carefully, they said Thanks for launching this course and some has watched first section, so they are telling so.
Great Ayush! You are the next Sundar Pichai and Satyam Nadela. This is what I found the basic gap in our primary education system. I also came from the same place but at the Age of 15, I was wondering how to clear my 10th Exam, and during graduation at 21, not able to write proper C-Programming. Just see his achievement and way of teaching style at 15. Thanks to his Mom and Dad for great learning to his son. Excellent Ayush.. God bless you Wish you for your bright future.
I see alot of comments talking about age, but let’s be real we clicked on this video because we wanted to learn. everyone’s life story is different, now get focused.
so true. Hes doing his best to teach and we should do our best to learn.
I agree with you mate.
No one is complaining about his age.
@@usuario5158 He never said that
this is how you get 18 years of experience at the age of 20
so true man
I dont know what i've done with my life xD. i'm 22
@@andersonjimenezsantana3309 Im a CS undergrad and now, I feel the same
@@andersonjimenezsantana3309 almost 22 and can do nothing, hi
@@andersonjimenezsantana3309 i wanna die XDD
Hats off to this man. I'm 27, 28 this year and I try changing my life, attending university and trying to follow valuable courses shared by fCC. Happy new year to everyone, hopefully your dreams and goals will be materialized this year!
I'm the same age as you. I'm trying to learn as much as I can to finally have a career
@@RobsMotivationHub Glad I am not the only one. Best of luck with pursuing your career!
good luck guys! lets keep at it😎
Me too, im 26
same here i am 25
The kid's 15. My god, look at the teaching skills and confidence at such age while delivering one of the hardest courses. He is gonna reach great heights ✌️✌️
For real.
And then there is me, a 22 year old CS majors learning from a 15 year old master. This is a proof that age is just a number, hats off to this guy may he fulfill all his dreams
I am 16 and I only know python and c++ 🌚🌝🌚🌝
Here I'm 21 just figured out that i can get input from html to python using flask from cs50 meanwhile he is teaching machine learning 😬 wth
Thanks, My Goal from this course is to deliver hardest in simple way and in very depth. I was working on this from the past 2 months,
0:00 - Intro
4:34 - Fundamentals of ML
25:22 - Supervised VS Unsupervised
35:39 - Linear Regression
1:07:06 - Logistic Regression
1:24:12 - Project: House price predictor
1:45:16 - Regularization
2:01:12 - Support vector machines
2:29:55 - Project: Stock price predictor
3:05:55 - Principal component analysis
3:29:14 - Learning theory
3:47:38 - Decision trees
4:58:19 - Ensemble learning
5:53:28 - Boosting, pt 1
6:11:16 - Boosting, pt 2
6:44:10 - Stacking Ensemble Learning
7:09:52 - Unsupervised Learning, pt 1
7:26:58 - Unsupervised Learning, pt 2
7:55:16 - K-Means
8:20:21 - Hierarchical Clustering
8:50:28 - Project: Heart failure prediction
9:33:29 - Project: Spam/Ham Detector
please, enjoy!
Thanks Man
merci bcp
Thank you 😊
Gracias papucho
Thank you for your kindness 👍
I'm over 30 and trying so hard to learn ML but still not able to grasp how to code. This is a punch in the face. All the best to this guy.
Seeing such a young kid with those skills, makes me proud of him and sad about me 😭
I am also 15 and have absolutely nothing on him...
Guys u know wot u can do it it's his story in which he stared early in yr story u can do whatever u want after all no 2 DNA matches 😁
Bro , just say your mind not to compare with him rather compare with past version of your self .
Either you focus on your education and career in your youth, or you focus on social life, hobbies/passion, rest/health or whatever makes you feel good ("living"). Either path you choose, you're going to have regrets when you're older because you didn't take the other path. This kid probably sacrifices things like social life, rest and other aspects of life that we focused on in our youth, which he might regret missing out on later in life just like we may regret not learning machine learning at 15. But it's really pointless to have regrets. You can still learn when you're older, or focus on what makes you happy.
Lol😂😂😂😭
Having done machine learning in the past year, this was actually a really good revision.
hi, can I ask how did you learnt ai/ml, and where do you work now
The youth of this guy and his knowledges inspired me to give up on everything.
Lol i read the description of this course and instantly started watching it until I saw this kid and F i gave up. 😢
😂😂😅
😂😂😂
Now a fetus teaching quantum mechanics please
🤣
😂😂😂
😂😂😂
LOL
a day will come for sure... 🤣 mostly schools or parents teaching only job oriented topics rather school life🤷♂️
4:56:00 Understanding decision trees is crucial for machine learning.
4:59:58 Recollection of high variance and high bias
5:02:08 Ensemble learning relies on the concept of majority vote.
5:06:30 Ensemble learning involves combining output from multiple models to improve accuracy.
5:08:32 Ensemble learning is widely used in industry and Kaggle competitions.
5:12:48 Bagging involves training models on subsets of the data and combining them for improved performance.
5:15:04 Sampling with Replacement in Supervised Learning
5:19:19 Bagging helps in reducing the variance
5:21:24 Bagging helps in reducing model variance.
5:25:38 Bagging technique helps in combining base models to reduce variance
5:27:41 Random forest is a combination of decision trees, bagging, and feature bagging.
5:31:52 Ensemble learning uses different models for higher accuracy
5:33:53 Using out of bag points for cross validation and model evaluation
5:38:09 Understanding Trivially Parallelized and Extremely Randomized Trees
5:40:20 Extremely randomized trees reduce variance using column sampling.
5:44:39 Using the Random Forest Classifier in scikit-learn
5:46:53 Explanation of various parameters in machine learning algorithm
5:51:08 RMSE is not default, you have to create your own function for it.
5:53:15 Boosting is a popular ensemble technique.
5:57:28 Bagging vs Boosting
5:59:35 Using boosting to reduce model bias.
6:03:32 Minimizing residual and fitting models for error reduction
6:05:32 Gradient boosting trains model to fit the residual from previous model
6:09:38 Gradient boosting is a powerful algorithm for improving error under training set.
6:11:50 Gradient boosting converts weak learners into strong learners.
6:15:46 Adaboost algorithm for machine learning
6:18:02 Training the model for boosting with residuals
6:22:28 Training data, loss function, and base learners in machine learning.
6:24:32 Regularization and shrinkage are used to address high bias and overfitting in boosting.
6:28:41 Implementation of Gradient Boosting Classifier
6:30:53 Adaptive boosting focuses on reducing overfitting with key hyperparameters
6:34:49 Learned about ada boost classifier
6:36:48 XGBoost is an advanced algorithm of gradient boosting
6:40:59 Regularization, construction algorithm, and parameter tuning in XGBoost
6:43:14 Introduction to Stacking in Ensemble Learning
6:47:44 Difference between bagging and stacking
6:49:54 Understanding bias and variance tradeoff in machine learning model tuning.
6:54:19 Ensemble Learning Techniques
6:56:32 Stacking is a method to train a second-level classifier on the predictions of base learners
7:00:47 Stacking classifier is better than random forest
7:02:50 Applying stacked classification using a grid search
7:06:51 Learned about ensemble learning
7:08:47 The course covers neural networks, GANs, and internships
7:12:50 Overview of unsupervised learning applications
7:14:48 Customer Segmentation for Personalized Recommendations
7:18:58 Unsupervised learning has applications in biology and business
7:20:53 Machine learning involves social network analysis and image segmentation with unsupervised learning
7:25:09 Outliers can be addressed using clustering algorithms like DBSCAN and isolation forest.
7:26:57 Introduction to clustering in machine learning
7:31:06 Segmenting data points into clusters
7:33:16 Optimizing intra and inter-cluster distances
7:37:40 Evaluation technique for clustering model
7:39:44 Understanding Cluster Evaluation Metrics
7:43:53 Introduction to clustering in machine learning
7:46:00 Exploring types of clustering
7:49:59 Hierarchical and Non-hierarchical clustering techniques.
7:52:06 Clustering is grouping similar objects with inter and intra-clusters.
7:56:08 Overview of k-means clustering with subtopics
7:58:24 Introduction to k-means clustering with 2 centroids
8:02:17 K-means clustering algorithm visualization
8:04:24 The K-means clustering algorithm involves cluster assignment and centroid re-calculation.
8:08:26 Understanding K-means clustering and distance calculation
8:10:21 Random initialization can cause clustering problems.
8:14:35 K-means clustering algorithm overview
8:16:33 K-means clustering limitations and time complexity
8:20:27 Introduction to Hierarchical Clustering
8:22:30 Clustering with example points P1, P2, P3, P4
8:26:38 Hierarchical clustering creates a hierarchy of clusters from individual data points.
8:28:40 Understanding divisive and agglomerative clustering
8:32:35 Understand the basic algorithm in agglomerative clustering
8:34:35 Approximating matrix approximation
8:38:39 Methods to measure similarity between clusters
8:40:46 The minimum approach finds the minimum distance and merges clusters accordingly
8:44:52 Explaining the process of merging clusters using distance comparison
8:46:48 Hierarchical clustering creates clusters by merging or splitting them based on distance
8:50:42 Build a heart failure prediction model
8:52:42 Building machine learning models for healthcare early detection and spam detection system.
8:56:34 Summary of data loading and basic exploration
8:58:32 Understanding business solutions through data analysis
9:02:23 Working with imbalanced data
9:04:27 Imbalance means that your data is not equally distributed between classes
9:08:33 Filtering and analyzing data in pandas
9:10:48 Observation about the number of cases and inference for age group 50+
9:15:06 Correlation values indicate linear relationship strength.
9:17:01 Data set development involves dividing data into training and testing sets.
9:21:00 Increase max iterations for non-converging data
9:23:06 Stochastic gradient descent is used to minimize approximation in machine learning.
9:27:05 Model evaluation techniques and parameter tuning
9:29:02 Optimizing model performance with randomized search
9:32:52 The Next project is about the spam detector system
9:35:08 Text-to-number conversion for machine learning model
9:39:22 Text cleaning is essential for data preprocessing.
9:41:31 Text preprocessing techniques like stemming and lemmatization
9:45:55 Stemming reduces inflection into words.
9:47:57 Converting text data into a numerical matrix for training
9:52:20 Introduction to basic concepts of machine learning
Now needed a 6 yr old teaching machine learning models!.
At this age we were messing around using paint application
At 10 i was still messing around with paint xD @ 15 i had moved on to Flash and PS ^^
@@mr.mikaeel6264 🤣🤣
At this age we were naughty 😂
@@mr.mikaeel6264 GTA SAN andreas is great
U know im 16 lol
As someone who is looking to break into this field, as an entrepreneur, and as a husband and a father, you are truly an inspiration. What you are doing is incredible and I wholeheartedly support you. Keep going. You are the future.
Same here
Yes but he needs to stop sounding like one of those call center people.
@@DoodleDoo Maybe you need to stop sounding like a racist
can you please tell me whether i should learn from here or opt a paid course. i am looking to learn in detail.
@@DoodleDoo man they r good people u should definitely do what they say
Please note:
at 53:56 , We multiply 1/m instead of adding to get Root mean square error.
Damn
Free code camp is a blessing💯
All the best to all budding coders out there!
Perfect example of age doesn't matter if you have knowledge
this is the perfect example of winning the genetic lottery... lmao... it has nothing to do with knowledge.... 🤣🤣🤣... No scientists have fully understood the brain yet.
@@ishananaguru exactly. Each person is different, and we can keep working on our ourselves to reach our potential, that upper limit will not be same between people and shouldn't be measured in the first place cuz there are a lot of variables which cannot be measured when it comes to the brain
I'm amazed at your intelligence and other Indian men! i once visited Delhi , a tired city full of tired people, but i was amazed by the intelligence and wisdom of the people! Thank you for your intelligence🙏
WOW I really needed this course for this semester and it just pops up at the perfect moment
Damn , he is so young and talented. Wish I had utilized my time in middle school 😞
Same.
Don't get discouraged, he obviously has impressive abilities, which the average person doesn't. But even if you procrastinated throughout middle school, it's never late to start and catch up. Don't think about it, just start(JUST DO IT!!!)
I'd almost wish that but internet wasn't really a thing i could access more than 10m a day during phys class while the teacher wasn't looking around so... No, i'd just wished i hadn't gave up on everything 15y ago when i got access to the internet and free knowledge like that :/
Better late than never however.
@@BiP00 Well said sir.
Same
Thank you so much for the video! very easy to follow. I graduated in a data science major but didn't learn it well back in the school. Your video picked up so much of my memories and helped me enhanced my ML knowledge. If there is a chance to go back to the collage, I won't waste my time on useless things and just focus on learning. Again, thank you for your effort on this video!
can you please tell me whether i should learn from here or opt a paid course. i am looking to learn in detail.
@@durveshdeore2746 df pay for courses online or in school if you start from the scratch. This video is more like a guideline or quick catchup
You've just saved my life bro. I really love ML but I was unable to understand the concepts of algorithms due to less interest in mathematical terms. but you are savior. You are teaching in really easy manner. For me on entire youtube u r the best teacher for ML. Just completed one hour of this video and going on.
I definitely learnt more ML in this video than during my whole year in Master's degree!
Are you serious ??
The kid's confidence just bamboozled me!!! Excellent course for the beginners!!!
You are just a sir my friend. So young and talented. Very proud of you. Wish you the very best in life.
I can’t believe I'm learning from a kid. Honestly I'm amazed and I'm really happy to learn from him.
And i am depressed seeing how I wasted my whole teenage 😐
@@devendr09 try not to overthink about it
@@devendr09 nah, I'd say it was worth it because of all the memories
I want this guy to be headlines of every news for all of which he has achieved in this age!
I've just started ML (supervised) at the age of 21 after having a mathematical degree. I feel ashamed after watching this video but happy cuz this guy explains things better than my PhD teacher .
We all have our own journey
brah im 21 and im just starting to learn fucking programming and ai stuff, dont worry lmao we have time
I'm here, at 26.
@@andredubbs4854 and here I am at 13 complaining about how I learned programming (python) too late
Generational change lmao everyone’s in a hurry ;)
I'm three times age this guy but I'm here to learn sir, hats off
The whole course is so comprehensive , thank you! This 9+ hours of knowledge tsunami actually represents a higher quality of teaching than some university courses in the same topic :D
That's my goal was in this course.
Just a questions, how is this course really? and is this for beginners, and if I am beginner what will be my level after completing this course. If I learn the content of this course well then will I qualified to join companies like MMAANG. (and ofcourse I know few other things as well)
@@ainovice6634 yes
@@ainovice6634 As the title of this video suggests this is a beginner's course, meaning that it gives you the fundamentals of machine learning. Landing a position at big companies (FAANG, MMAANG, or whatever acronym you use) requires specialized knowledge which could further require years of experience and a degree from a university or an educational institution. You can treat this course as the first step towards becoming a specialist in the field
evarra nuvvu intha talented gaa vunnavu
I will be honest - I've first wanted to switch to another video just by lookig at how young the lecturer is. But I've decided to keep watching and I totally love the way the lecturer explains things.
He's So Mature and intelligent.
I watch this video in tears
Hats off to you.. Really impressing teaching and your knowledge... Many students don't know what to do with their career even after their graduation...
And as always thank you free code camp. He's so inspiring!!!!!
55 mins into the course, all i can say is this guy is genius, he teaches perfectly
Love from India Ayush❤️😍. Keep going brother and teach more like this.
Thanks
@Abhay Bisht CSDS Hi I already started in my channel, If you see ML002 ( It starts from teaching linear algebra, calculus, probability theory and stats ), Search for ML002 Newera, U will get that!
Need to find a new definition for 'generation gap', awesome 👍
The instructor just motivated me
This kid will have great future ahead!
*has
Feel very proud of him. And feel very old too. Hats off to this prodegy.
@@prathameshdusane2619 Hi, I am from Patna, Bihar, India, I never gone outside india.
Danke!
5:44:00 Random Forest Implementation, Revisit for hyperparameter tuning. 6:16 GBM
I'm grateful that the future of ML is in good hands
Wow, I usually have a difficult time understanding Indian English accent but you speak so clearly and well that I didn't have trouble understanding at all.
wow i never thought that a kid would be my teacher . but he is far more better than my collage professor .
Now this is what education should be like.
I just want to point out, while this course is amazing, and it's crazy how much this dude knows (I mean, he looks like 16 years old or something), there's quite a lot of inaccuracies in the equations and way he formulates problems. Makes me think he "memorised" the maths, rather than actually try to understand them.
what do you expect from a 14yr old who's trying to clear his 8th class
Feeling sad about yourself?
@@okonkwo.ify18 was that directed at me?
@@carlosmspk yea to your cappuccino head
@@okonkwo.ify18 In that case, no, I'm feeling rather happy, but sometimes I feel sad about myself... Like most people, I guess...
00:01 must be a great course, it's starts at the beginning. Always a good idea
lol
Scamed us😂😂🤣
☠️
GOD BLESS YOU AYUSH ALWAYS...........you a school kid is a big motivation for engineers......
huge thumb's up to this video, damn. i love this channel, these teachers are so helpful
He made my name spread all over the world. I am very proud of you 😂
I’m buying a hoodie as soon as I can. Need to support this amazing channel 🙌🏼
Your confidence and english really impressed me. Boy you are really an inspiration
Another fantastic offering: liked and subbed to your channel Ayush. Thank you!
I am using this course for my GATE DA prepration It really is great.
Compliments. Wish I had started teaching at this kid's age! 😀
Age is just a number the thing which matter is the knowledge, you proved this bro
So this is what feeling old is like...
Good job by the way! Extremely educational!
hahaha brooo :c so sad i'm 23 and feel old next to this guy :c
Such a wonderful person. Who wishes to teach Machine Learning for us .He wish to do things like Ratan Tata.....U will reach More than that Mr Ayush......
In LInear Regression , the cost funtion is 1/m * (summation of square of difference between ground value and predicted value).But in the tutorial you wrote 1/m + (summation part). Change it. Other than that your video is awesome.
100% true
Yessssss I just ask ChatGPT a same Q !!!!!!
Lots of love From Kashmir ....♥️
better explanations than my professor at Uni
This kid is now my inspiration. No he is not a kid. He is much more
⭐ Course Contents ⭐
⌨ (0:00:00) Course Introduction
⌨ (0:04:34) Fundamentals of Machine Learning
⌨ (0:25:22) Supervised Learning and Unsupervised Learning In Depth
⌨ (0:35:39) Linear Regression
⌨ (1:07:06) Logistic Regression
⌨ (1:24:12) Project: House Price Predictor
⌨ (1:45:16) Regularization
⌨ (2:01:12) Support Vector Machines
⌨ (2:29:55) Project: Stock Price Predictor
⌨ (3:05:55) Principal Component Analysis
⌨ (3:29:14) Learning Theory
⌨ (3:47:38) Decision Trees
⌨ (4:58:19) Ensemble Learning
⌨ (5:53:28) Boosting, pt 1
⌨ (6:11:16) Boosting, pt 2
⌨ (6:44:10) Stacking Ensemble Learning
⌨ (7:09:52) Unsupervised Learning, pt 1
⌨ (7:26:58) Unsupervised Learning, pt 2
⌨ (7:55:16) K-Means
⌨ (8:20:21) Hierarchical Clustering
⌨ (8:50:28) Project: Heart Failure Prediction
⌨ (9:33:29) Project: Spam/Ham Detector
What's with the keyboard emojis?
I appreciating free code camp, I have seen many videos, code camp always encouraging developing people, like a flask, NLP everywhere,
thankyou so much, all are want this kind of help, you will develop too faster, that's the boon from my side.
This kid is freaking 15, just checked out his channel and damn. He already knows data structures and algo's, GANs and other complex ML algorithms not just by code but also conceptually with is what is harder to grasp.
Good boy!
Even post graduate didnt know that! 😂😂
Proud of my fellow 15yo, sadly I am nowhere near his level at AI, but I am a competitive programmer which is a lot less cool, but I'll take it!
@@rareshika everyone is cool bro. Don't under estimate
I can't seem to find the notebooks used in this tutorial. Can anyone help me?
congratulations young man. im almost 30 and i feel so inspired right now i feel like crying i swear people are amazing
Благодарим ви!
This video helps me a lot to start machine learning. Hats off to this young man. BTW, Could we access to the lecture slids? That will be great helpful.
Note:
At 50:20 the correct is (pred - act)^2 because if u calculate (pred - act) and sum for all x, the points above, and the points below will cancel each other, since (pred - act) < 0 if act > pred and (pred - act) > 0 if act < pred.
Aren't residuals actual-predicted not predicted-actual?
Thankyou for this course. I learned a lot.
just a few suggestions:
1) Stop the accent.
2) Clearity of thought needs to improve.
3) Improve spoken english.
with that being said, I appreciate your efforts and salute you for your expertise.
yea sometimes he goes "theyta" and when things get a little complex he reverts to "theeta" lmfao
My mind is super blown. Super happy for you! 🎉
This kid is like the next "tech with Tim"
Thank you. This was a great and fun course from the first minute to the last minute.
At 15 I was learning the birthdays of ancient rulers 😢😆😆
🤣
Ikr the education system sucks
even people at the age of 28 do learn in india
@@dynamixthunder724 even people of age 32 do that... UPSC candidaes
Failed education system and Judiciary of India
This kid is bringing singularity to our world
This dude is what every Asian parents want 15 years old with 20 years experience
"Mom, just one video before sleep"
"Ok, son".
im ded 😂😂😂😂😂😂😂😂😂😂😂😂😂😂😂😂😂😂😂😂😂
btw : my own mom has experienced sth similar with older brother.. so now she never allows even one vid 🤣
when someone is younger than you but way smarter than you ; this is enough to get MOTIVATED !!!
Imma listen to this kid.
I have a little question, in the whole calculation of RMSE in linear regression , why are we addting 1/m instead of multiplying it by 1/m. Even if we consider the units of the entities, we are trying to add a number with distance .
You're correct, this is an error.
came here looking for this comment
yeah also was troubled by this, we need to multiply by 1/m not add.
Yep it’s the average of the squared error. Bad mistake.
correct. In fact, for the unbiased one you multiple by 1/(m-1)
Really Waiting for this. Thank You..
At his age I used to close my refrigerator’s door slowly and peak to see if light goes off 😆
I still do that at 23 😆
Can i just get this mans knowledge transplanted into my head. Via machine learning?
You are so young and talented , both at academic and teaching
bhai mera duniya sey vishwaas uth chuka hai
Why ?
its very inspiring to see a child knowing so much about machine learning .
Ayuuuuushhhhhhh !!!! Ooooooo my goddddddd...... amazing ❤❤❤❤🥺
Gracias por compartir tu conocimiento con nosotros you are amazing
Thanks man it was really helpful
thanks man it was really helpful
Am also of same age as Ayush and this video is an eye opener for me that where I actually stand in coding community. I have to learn a lot....Btw, waiting for this video :)
You are lucky. You have time on your side! At 15, don't smoke. Don't drink. Party less. Don't play video games. Live, breathe, and sh.. Data Science/Mathematics/CS. You can do it. The world is your oyster!!
@@experiment0003 hey buddy, thanx for the motivation :)
same :)
@@experiment0003 agree but "don't play video games"? a healthy amount of video gaming is good for the brain c'mon.
@@darkreaper4990 I agree 100%! I meant don't lose yourself in video games! I actually still play chess almost every day or my life. As a kid, I played on my Atari, nintendo, snes, playstation, etc. So, I support video games!
You are so young! I’m jealous of your knowledge level
10h tutorial uploaded 5h ago, and yet people are thanking him for best course they ever had. I mean come on people... Did you watch it on 2x speed and made 0 notes or took no breaks at all? What's the viability of your comments. It rather sound like a fanboys trying to get their comments to the top ...
Hey, Don't take it in wrong way, Plz read the comments carefully, they said Thanks for launching this course and some has watched first section, so they are telling so.
It’s amazing that even young people like me can learn Programming for free on the Internet.
This is literally the best tech channel on youtube
Exactly the course I've been looking for!!!
Thousands of lives will change after this... 😀
I was eagerly waiting for this..
Thank you very much sir...
Great Ayush!
You are the next Sundar Pichai and Satyam Nadela.
This is what I found the basic gap in our primary education system. I also came from the same place but at the Age of 15, I was wondering how to clear my 10th Exam, and during graduation at 21, not able to write proper C-Programming.
Just see his achievement and way of teaching style at 15. Thanks to his Mom and Dad for great learning to his son. Excellent Ayush.. God bless you
Wish you for your bright future.
No , He's next Larry Page and Bill gates
Nope, he is himself in the future
Absolutely well done and definitely keep it up ❗👍👏👍👏👍👏👍
Deadly Tech combination that almost guarantees skills.
Indian & Man