Thanks a lot to apni kaksha team......fir this video......I request to the team to guide us regarding the sem wise road map for mastering in ML and AI similar to which was made for software and web development
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more. [ According to me once you should visit if anything is missing then comment their I will improve that ]👍
Sir uh guys are really providing the valueable knowledge that no one does for free they take much money for money sir heads off to you and your team really appreciate uh guys. Nothing is beyond than providing knowledge and uh guys are really good at that. I really can't explain my feelings on same. Sir my college is taking around 10lac for cs btech and they haven't taught us the c language but uh guys did that in time that was c++ for free I mean uh guys are amazing 😍🤩👍
Mathematics for ML is a step ahead of what we learn in class 11 and 12. For ex. we are only taught derivatives of functions w.r.t to a single variable in class 11/12. For ML, we have gradients of vectors w.r.t matrices ( or vice-versa ) which yield tensors.
@@techkid358 For ML you'll need: Probability (Bayes rule, expectation, different distribution both discrete and continuous valued) Matrix Calculus (particularly useful in Neural networks) Python (libraries like Scikit learn, numpy, pandas, matplotlib, seaborn, tensorflow or pytorch) - no need to be an expert. Agar thoda practical jana hai to: Web scraping Data cleaning and exploratory data analysis Thodi bohot statistics. - Sab kuch aane ki zarurat nahi hai. Main thing is Python, probability, and matrix calculus
I have to give feedback after listening to your lectures that all the videos created by your team is so simple that non-IT background person can also learn to code. While doing in-hand projects with coding understanding . 👍🏻
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more. [ According to me once you should visit if anything is missing then comment their I will improve that ]👍
Start learning it from learning python. If you need best resources for starting your journey. Let me know. I just completed my learning in just 5months
@@ankurgupta7102 thanks for the advice. I'm entering my final year and my current status is: I know python, numpy and pandas. I want to learn ML just for the sake of projects. IDK if I should go further with this because I have just started with coding and DSA.
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more. [ According to me once you should visit if anything is missing then comment their I will improve that ]👍
Thank you ma'am for this video. It's really very helpful for me and many others. Keep uploading these kind of videos always. It keeps us updated with the world Thank you
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more. [ According to me once you should visit if anything is missing then comment their I will improve that ]👍
One of the most important things that's required in the real world Data Science jobs and that comes under data pre-processing is good old SQL Thats missing from your video. - Data Scientist here
You need to have all Skills require dfor Mechanical, Electrical and Computer science student i.e you Need to know all programming language and You must know about Circuits and all and You must have proper knowledge about Mechanical systems. By the way I'm pursuing B. Tech in Mechatronics Engineering
Pata hai sabse achi baat kya hoti hai apke videos ki? KI aaplog "like kare,share kare,subscribe kare" wala cheez nahi karte ho. Isliye videos dekhne ka interest aur bhi zyada badh jaata hai aur ab toh Aman bhaiya ne ads bhi hata diye hai. Bhaiya ek do ads hmlog dekh lenge aap daal sakte hai. Apki videos itni worth hoti hai. Thank you to the whole Apna College Team! You guys are doing something very amazing.
😀💯🧠 keep going guys @apnacollege @apnikaksha make India's education better than Harvard/Stanford. Bring back those days when people from all over the world used to come here to get education. ❣🌹🙇♂️😊 GOD BLESS ALL OF YOU 😇
I will give my 100% to sharp my skills and life mey ek baar muka mile aaplogo ke saath kaam karneka and aur bhi bahut kuch sikhne ka... you guys are GREAT!!!!!!
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more. [ According to me once you should visit if anything is missing then comment their I will improve that ]👍
This video was really so much productive and use full for me. I loved it so much I just now started watching your videos and thanks for motivating. And can you please make Road map on Artificial Intelligence and Learning part too.
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more. [ According to me once you should visit if anything is missing then comment their I will improve that ]👍
DIDI THANK YOU VERY MUCH.. VERY MUCH... AAPLOG KITNA DHAYAN DETE HO SAB COMMENTS PAR.. MEYNE APKE KE VIDEO MEY YAHI COMMENT KIYA THA KI PLS ML PAR EK PROPER VIDEO BANA DIJIYE.. AND AAPLOG NE 3 DIN MEY BANA DI..... BIG SALUTE TO APNA COLLEGE .... LOTS OF LOVE AND RESPECT.
🎯 Key Takeaways for quick navigation: 00:13 🎓 *Introduction to Machine Learning Basics* - Overview of important algorithms and topics in machine learning. - Essential for research, projects, and data science job interviews. - Machine learning applications in everyday scenarios like online shopping and email filtering. 01:09 🤖 *Connection between Machine Learning, Algorithms, and Data* - Explanation of how machine learning combines algorithms and vast amounts of data. - Examples of companies like Amazon, Google, and others using machine learning with extensive data. - Emphasis on the role of algorithms and data in the machine learning process. 02:02 🌐 *Resources and Learning Plan* - Discussion about additional resources for learning machine learning. - Introduction to an extensive list of resources for further exploration. - Importance of defining goals and creating a learning plan for successful machine learning education. 03:09 📘 *Customization in Machine Learning Research Projects* - Discussion on customization for students involved in machine learning research. - Considerations for customizing based on whether the focus is on product development or research. - Importance of defining goals and specifications for algorithmic work in research projects. 03:38 🧠 *Importance of Deep Understanding in Algorithmic Work* - Emphasis on the need for a deep understanding of algorithms and how they drive projects. - Mention of libraries that handle extensive algorithmic work and the importance of reducing library reliance. - Encouragement to delve into the code, understand algorithmic specifics, and pay attention to algorithmic trends. 04:18 🎓 *Prerequisites in Mathematics for Machine Learning* - Overview of essential mathematics topics for machine learning, including linear algebra and statistics. - Advice for individuals with science or commerce backgrounds to refresh basic math knowledge. - Recommendations for accessing online resources and videos to learn or revisit foundational math concepts. 05:00 📚 *Learning Path in Python and Key Libraries* - Importance of learning Python and basic typing skills as a prerequisite. - Introduction to crucial libraries, NumPy and Pandas, for efficient data manipulation and analysis. - Emphasis on the ease of logic conversion and job prospects after acquiring these Python skills. 05:41 🚀 *Transition to Core Machine Learning Concepts* - Importance of transitioning from Python fundamentals to machine learning concepts. - Introduction to core machine learning topics: Supervised, Unsupervised, and Reinforcement Learning. - Recognition of the heavy content within machine learning and its foundational elements. 06:10 📊 *Key Concepts in Machine Learning Core* - Overview of essential terms: Supervised learning, Unsupervised learning, and Reinforcement learning. - Mention of the significance of understanding these terms within the machine learning core. - Highlight of specific algorithms related to these core concepts, such as Linear Regression. 06:53 🧐 *Metrics and Evaluation in Machine Learning* - Discussion on important metrics in machine learning, including Overfitting, Underfitting, and Regularization. - Introduction to tools like Confusion Matrix for assessing algorithm performance. - Illustration of real-world examples, like cancer detection, to emphasize the relevance of choosing the right algorithm based on performance metrics. 07:34 🎯 *Decision-Making Based on Algorithm Performance* - Explanation of how performance metrics guide decision-making in algorithm selection. - Importance of confidence in algorithms and adjusting volume based on their reliability. - Reference to the famous professor Andrew Ng's ML course and its significance for learners at different levels. 08:46 🌐 *Importance of Data Preprocessing* - Introduction to the significance of data preprocessing in machine learning. - Explanation of how major components like handling missing values, converting data types, and standardization contribute to data quality. - Emphasis on the role of data preprocessing in improving the accuracy of machine learning models, using cancer detection as an example. 09:26 🧹 *Techniques in Data Preprocessing* - Overview of techniques involved in data preprocessing, including handling missing values and converting string values to numbers. - Importance of standardization, categorizing, and feature scaling in the preprocessing stage. - Significance of gaining practical knowledge in data preprocessing for effective machine learning projects. 10:09 🛠️ *Advanced Data Preprocessing Techniques* - Introduction to more advanced data preprocessing techniques, such as handling categorical values, feature engineering, and feature scaling. - Explanation of the importance of understanding feature scaling and feature engineering for machine learning. - Emphasis on the role of these techniques in preparing data for ML libraries like Tensorflow, making complex projects easier. 11:07 📚 *Leveraging ML Libraries for Simplified Projects* - Discussion on using ML libraries, focusing on Google's TensorFlow. - Reference to the abundance of pre-built models within libraries and their application in diverse projects. - Encouragement to explore and utilize available ML libraries to simplify and enhance the machine learning project creation process. 11:19 📊 *Exploring Machine Learning Resources* - Introduction to libraries like NetPlotLib for visualizing data in machine learning algorithms. - Mention of Google's TensorFlow library and the wealth of deep learning resources available within it. - Reference to the importance of exploring and utilizing available libraries for effective machine learning. 12:00 🧠 *Understanding Qualifications in Machine Learning* - Discussion on qualifications and specializations in machine learning, drawing an analogy with medical studies. - Introduction to the qualification path in machine learning, highlighting the importance of understanding neural networks. - Reference to advanced topics and resources available within the field, emphasizing the depth of knowledge required. 12:41 🌐 *Learning Platforms and Datasets* - Recommendation of different websites and platforms for learning machine learning, including available datasets. - Highlighting the availability of comprehensive resources on specific websites and providing a reference link. - Encouragement to practice and participate in contests on platforms to gain practical experience. 13:23 🚀 *Building Projects and Research Opportunities* - Guidance on progressing from learning to building innovative projects and potential startup ideas. - Suggestion to explore research opportunities, referencing organizations like DARPA. - Introduction to applying for research programs, indicating options within institutes and organizations. 14:05 🎓 *Connecting with Research Students in IT* - Encouragement to connect with research students in the IT branch of science. - Suggestion to visit college campuses, showcase machine learning projects, and engage with students. - Emphasis on building a network and collaborating on research projects with students who have expertise in machine learning. 14:33 🧠 *Importance of Learning Essential Algorithms* - Highlighting the significance of learning essential algorithms for a strong foundation in machine learning. - Reference to crucial topics that are essential for mastering machine learning. - Providing links to important resources and algorithms for continuous learning and improvement. Made with HARPA AI
@@omgor2806 q ki channel aman bhai ka h,didi to job kar rhi h 🤓,so jisaka channel hota h vhi jwab deta h, password usake pas hi hote hn ☺️... Kya bhai y b nhi pta🤓 Sb aman bhai hi krate hn, unke khane pe hi to y wo topic pdaynge....
A line by aman bhaiya I have edited it somehow😁 "Yaar yeh didi mtlb yeh didi toh chah h na " 😁 Mst btaya didi mujhe blockchain developing m jaana h and really appreciate you
Your's explanation is awesome and impactive, if possible plz make another vedio which will contain the approaches and goal towards "artificial intelligence"..
01:53 Machine learning is the combination of data and algorithms used in various technologies like Amazon, Google Assistant, etc. 03:46 Define your goal before learning machine learning 05:39 To learn machine learning, first, understand basics math, then learn Python and its libraries. 07:32 Python basics and important algorithms of machine learning 09:25 Algorithm selection based on accuracy is important in cancer detection 11:18 Data preprocessing is crucial for machine learning algorithms 13:11 Skykit learn, Matplotlib, and Tensorflow are important resources for machine learning and deep learning. 14:59 Explore opportunities in machine learning and advance your career.
Please make one more video based on how to approach for an interview where there is demand of machine learning and how to apply for internships as well in this field :)
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more. [ According to me once you should visit if anything is missing then comment their I will improve that ]👍
Its always difficult to find resources in ML which includes maths along with its coding part.... I didn't get satisfactory course till now (its always like I missed something)... hoping this might help.🙂
For machine learning it's necessary to learn maths behind algorithms to tune hyperparameters for getting good accuracy Didi har jgah gyan nai pela jata ki maths krne ki zrurat nai🙂🙂
Listen first with ur ears open bro. She said about the goals related to product or algo. It is clear from her statements that heavy maths is needed for algos..
Vote for complete ML playlist ❤
Microsoft waali didi is Rocking yaar!!!😌🙌🏻✌🏻👌🏻👌🏻
@@suryathereader3567 *shraddha
@@suryathereader3567 Linkidn yaa koi aur account hai eska?
She should put "Known as Microsoft Wali didi by Millions of people" in linkedin
@@ankushverma2894 tere aukad ke bahar hai didi ki fees
@@devanshgupta4279 sale tere kyu faat rahi hai.....
"If you don't sacrifice for what you want, what you want becomes the sacrifice", awesome quote by Aman bhaiya.
I heared this quote from Physics Wallah sir
I remember this ❤️ Aman Sir Op 🔥🔥🔥
This is not Aman Bhaiya's quote
@@melomaniac7444 Jealous?
Bhai aman dhatarwal ne nhi kaha hai ye , aman bhaiya ne sirf use kra
Microsoft wali didi is taking hearts nowadays😂😂❤
Bhaiya Didi ke saare videos ka alag se playlist banwa do😂❤
😂😂😂😂
Play list ka naam Microsoft wali didi😅
@@sameerjadhav3044 Lol😂😂
Simp
@@kumaraayush"Didi" Saala Gadha🤢
literally needed as I am beginning now😁❤️. Thanks to you all.
have you learnt it now?
@@priyanshirawatmusichave you learn it if yes please guide me
Have you learned it yet bro
Hare Krishna Hare Krishna Krishna Krishna Hare Hare Hare Rama Hare Rama Rama Rama Hare Hare
Thanks a lot to apni kaksha team......fir this video......I request to the team to guide us regarding the sem wise road map for mastering in ML and AI similar to which was made for software and web development
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more.
[ According to me once you should visit if anything is missing then comment their I will improve that ]👍
Didi please make the roadmap to cloud computing in next video🙏🙏🙏🙏
Cloud computing is a glorified remote computer.
kya explain kiya hai....OSM❤️👍
Complete Machine Learning course in hindi :- ua-cam.com/play/PLu4yXgpA6Wg5HTUfU4xh8eN5E8hpmRCNK.html
Thanks for the information didi!!!😄❤️🔥👍👏🏽🙏🏼
BBA student can do something in this field
we need video on data scientist and roadmap , resoures, placement etc on it ...... Plz upload it Asp
Yes
yes please
You guys are taking education on the next level. Keep up the great work
Thanks
microsoft didi aap outstanding hai..!:))
Sir uh guys are really providing the valueable knowledge that no one does for free they take much money for money sir heads off to you and your team really appreciate uh guys. Nothing is beyond than providing knowledge and uh guys are really good at that. I really can't explain my feelings on same. Sir my college is taking around 10lac for cs btech and they haven't taught us the c language but uh guys did that in time that was c++ for free I mean uh guys are amazing 😍🤩👍
❤️e
Mathematics for ML is a step ahead of what we learn in class 11 and 12. For ex. we are only taught derivatives of functions w.r.t to a single variable in class 11/12. For ML, we have gradients of vectors w.r.t matrices ( or vice-versa ) which yield tensors.
Can u explain in detail plezz
I m taking AIML this year.. I m little bit of afraid that mujhse ho payega ya nhi
@@techkid358 For ML you'll need:
Probability (Bayes rule, expectation, different distribution both discrete and continuous valued)
Matrix Calculus (particularly useful in Neural networks)
Python (libraries like Scikit learn, numpy, pandas, matplotlib, seaborn, tensorflow or pytorch) - no need to be an expert.
Agar thoda practical jana hai to:
Web scraping
Data cleaning and exploratory data analysis
Thodi bohot statistics.
- Sab kuch aane ki zarurat nahi hai. Main thing is Python, probability, and matrix calculus
@@manhalrahman5785 ohh thqu for this I will remember this in my future
@@techkid358 ड
@@manhalrahman5785 thank you bro, what about Linear algebra ...exactly which topics should we learn?
Very soon launching new channel. Apni didi. 😂😂😂😂
Okhh
Didi bhaiya
apni microsoft wali didi
What's her name ?
@@amiya51 shraddha didi
I have to give feedback after listening to your lectures that all the videos created by your team is so simple that non-IT background person can also learn to code. While doing in-hand projects with coding understanding . 👍🏻
sir i am nit warangal student . I am preparing for data analyst , can we apply in canada
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more.
[ According to me once you should visit if anything is missing then comment their I will improve that ]👍
Thanks for this video, I'm starting the journey.
Can we do learn together 🤗
Hi
How are you
Start learning it from learning python. If you need best resources for starting your journey. Let me know. I just completed my learning in just 5months
@@ankurgupta7102 thanks for the advice. I'm entering my final year and my current status is: I know python, numpy and pandas. I want to learn ML just for the sake of projects. IDK if I should go further with this because I have just started with coding and DSA.
Are yaar background me music mt do bahut irritating hai
Thanks for being with us 😁
Her experssion is lovely the way she express any topic is Really appreciation.....😍😍
intro bhaut acha lagta ha "Hello Everyone"😎😎😎😎😘😘😘😘
7:06 when she said " board cancel hone se pelhe " savage 😂
Is borad is cancelled forever?
@@abhishekshub nahi bahi bass is saal
Provided* iss saal Corona khatam hota h
@@HimanshuYadav-qy5smcorona waale day yr 🙂🤌
Hello. I am also uploading Machine Learning Course. Check mine also. Thanks alot. For your cooperation ❤❤
@@abhishekshubHello. I am also uploading Machine Learning Course. Check mine also. Thanks alot. For your cooperation ❤❤
Each student should get Mentor like you, great work you are doing by simplifying subjects, topics , terms for us. Thanks a mile Mam🙏
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more.
[ According to me once you should visit if anything is missing then comment their I will improve that ]👍
Thank you ma'am for this video. It's really very helpful for me and many others.
Keep uploading these kind of videos always.
It keeps us updated with the world
Thank you
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more.
[ According to me once you should visit if anything is missing then comment their I will improve that ]👍
Great guidance 😇 Thank you Ma'am and Aman Viya
Thank you so much shradha didi because best explain for ml beginning students , you show us first to end for ml
One of the most important things that's required in the real world Data Science jobs and that comes under data pre-processing is good old SQL
Thats missing from your video. - Data Scientist here
Bro may i know how is data science career.
Hey ma’am, can u plz brief us about Robotics and necessary skills required for Robotics engineering
@ApnaCollege
You need to have all Skills require dfor Mechanical, Electrical and Computer science student i.e you Need to know all programming language and You must know about Circuits and all and You must have proper knowledge about Mechanical systems.
By the way I'm pursuing B. Tech in Mechatronics Engineering
see IISc robotics curriculum for more info
Microsoft waali Didi Thank you sooooooooo much🔥🔥
Bola aur jaldi se hi video bhi aagaya. ❤️
Thank you so much Shradha for explaining the way to learn ML in so simple words.
Have you learnt ml qnd built projects?
@@kundanpatle2761 No, dude. Just caught up with current work. How about you? Can you share if you started with this?
Didi itne confidence de bolti h ki lgta h ki ye kerne me pura benefit h
Didi ki ekk vedio bhe me miss nahi kerta
Salute to didi 🙏🙏🙏🙏
Didi ko bolta hu ek English ka course bhi daldo
A big shout out for shraddha di ❤️, doing great work di 👌😊
Pata hai sabse achi baat kya hoti hai apke videos ki?
KI aaplog "like kare,share kare,subscribe kare" wala cheez nahi karte ho.
Isliye videos dekhne ka interest aur bhi zyada badh jaata hai aur ab toh Aman bhaiya ne ads bhi hata diye hai. Bhaiya ek do ads hmlog dekh lenge aap daal sakte hai. Apki videos itni worth hoti hai.
Thank you to the whole Apna College Team! You guys are doing something very amazing.
Ads lage hai par akhri me
Please make video for Roadmap on Data Science ✌️😅❤️
Microsoft wali didi is best didi mere liye to God he ............🤩
😀💯🧠 keep going guys @apnacollege @apnikaksha make India's education better than Harvard/Stanford. Bring back those days when people from all over the world used to come here to get education. ❣🌹🙇♂️😊 GOD BLESS ALL OF YOU 😇
PLEASE MAKE A VIDEO ON THE ROADMAP FOR GAME DEVELOPMENT USING PYTHON & CAREER OPPORTUNITIES IN IT & REQUIREMENTS, COURSES ETC.
If possible, please make a roadmap video on cyber security as well.
Regards
Yaar yeh kitti awesome hai yaar 😍😍😂
Didi u r so beautiful as well as very helpful. THANK YOU DIDI🙏🏻🙏🏻❤️❤️
Sabka ek aim hota hai ..
I want to now prove myself to be a part of apni kaksha.
I will meet u aman ... That day will be a success for me
I think this is roadmap for becoming data scientist and not just ML.... Great video
Samjhane ka tarika bohot achchha hay. Achchhe teacher hay aap.
Really you people are gold mine 🙏🙌
I will give my 100% to sharp my skills and life mey ek baar muka mile aaplogo ke saath kaam karneka and aur bhi bahut kuch sikhne ka... you guys are GREAT!!!!!!
All about Cloud computing....
And how to start career in this field 🙏🙏
software engineering ke road me video bnao mam pls.,, aap achii tarah se , step by step samjhate h, thank u mam
Ma'am could computing roadmap!!
Yess mam please
Do you mean cloud computing?
@@herambpatilofficial Yaa
Yes please
Hello team Apni Kaksha, make a video on game development too please .
Didi Iam pass out from 12th and now I want to learn coding how and from where I start please tell mee ☺️☺️. Love your videos ❤️☺️❤️
Thanku to Apna collage it will help us a lot in knowing all these things better ❤️❤️🙏🙏
Thank you apni kaksa for this amazing video.
Microsoft wali Didi.. explains too well🤗😋
Thank you so much for everything!!!🙏
One of the best channel for (Ai) on UA-cam is (indian ai production).....
You will learn important libraries and ml algorithm....
this level of guidance is really appreciated
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more.
[ According to me once you should visit if anything is missing then comment their I will improve that ]👍
Krish Naik is best video playlist on you tube for Machine Learning and Deep Learning 🔥
Nice video apna clg team....thanks for giving those type of videos and it's really help us a lot...
I am your regular student 😀
Bhai data science university exam pass karne ke liye koi resource hain toh batao naa pls,
Love you Microsoft wali Didi ❤️
My college professor only knows "star pattern and the sum of two numbers". hardest part is star pattern ☺
Now a days there are a lot of places from where you can learn. You no longer have to depend on your college for your knowledge
Superb!!! Thanks for all the explanation!
Maybe world is listening to my doubts
Because I am getting answers everywhere
Maam your explanation is amazing.✨❣️
Hi
This video was really so much productive and use full for me. I loved it so much I just now started watching your videos and thanks for motivating. And can you please make Road map on Artificial Intelligence and Learning part too.
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more.
[ According to me once you should visit if anything is missing then comment their I will improve that ]👍
DIDI THANK YOU VERY MUCH.. VERY MUCH... AAPLOG KITNA DHAYAN DETE HO SAB COMMENTS PAR.. MEYNE APKE KE VIDEO MEY YAHI COMMENT KIYA THA KI PLS ML PAR EK PROPER VIDEO BANA DIJIYE.. AND AAPLOG NE 3 DIN MEY BANA DI..... BIG SALUTE TO APNA COLLEGE .... LOTS OF LOVE AND RESPECT.
🎯 Key Takeaways for quick navigation:
00:13 🎓 *Introduction to Machine Learning Basics*
- Overview of important algorithms and topics in machine learning.
- Essential for research, projects, and data science job interviews.
- Machine learning applications in everyday scenarios like online shopping and email filtering.
01:09 🤖 *Connection between Machine Learning, Algorithms, and Data*
- Explanation of how machine learning combines algorithms and vast amounts of data.
- Examples of companies like Amazon, Google, and others using machine learning with extensive data.
- Emphasis on the role of algorithms and data in the machine learning process.
02:02 🌐 *Resources and Learning Plan*
- Discussion about additional resources for learning machine learning.
- Introduction to an extensive list of resources for further exploration.
- Importance of defining goals and creating a learning plan for successful machine learning education.
03:09 📘 *Customization in Machine Learning Research Projects*
- Discussion on customization for students involved in machine learning research.
- Considerations for customizing based on whether the focus is on product development or research.
- Importance of defining goals and specifications for algorithmic work in research projects.
03:38 🧠 *Importance of Deep Understanding in Algorithmic Work*
- Emphasis on the need for a deep understanding of algorithms and how they drive projects.
- Mention of libraries that handle extensive algorithmic work and the importance of reducing library reliance.
- Encouragement to delve into the code, understand algorithmic specifics, and pay attention to algorithmic trends.
04:18 🎓 *Prerequisites in Mathematics for Machine Learning*
- Overview of essential mathematics topics for machine learning, including linear algebra and statistics.
- Advice for individuals with science or commerce backgrounds to refresh basic math knowledge.
- Recommendations for accessing online resources and videos to learn or revisit foundational math concepts.
05:00 📚 *Learning Path in Python and Key Libraries*
- Importance of learning Python and basic typing skills as a prerequisite.
- Introduction to crucial libraries, NumPy and Pandas, for efficient data manipulation and analysis.
- Emphasis on the ease of logic conversion and job prospects after acquiring these Python skills.
05:41 🚀 *Transition to Core Machine Learning Concepts*
- Importance of transitioning from Python fundamentals to machine learning concepts.
- Introduction to core machine learning topics: Supervised, Unsupervised, and Reinforcement Learning.
- Recognition of the heavy content within machine learning and its foundational elements.
06:10 📊 *Key Concepts in Machine Learning Core*
- Overview of essential terms: Supervised learning, Unsupervised learning, and Reinforcement learning.
- Mention of the significance of understanding these terms within the machine learning core.
- Highlight of specific algorithms related to these core concepts, such as Linear Regression.
06:53 🧐 *Metrics and Evaluation in Machine Learning*
- Discussion on important metrics in machine learning, including Overfitting, Underfitting, and Regularization.
- Introduction to tools like Confusion Matrix for assessing algorithm performance.
- Illustration of real-world examples, like cancer detection, to emphasize the relevance of choosing the right algorithm based on performance metrics.
07:34 🎯 *Decision-Making Based on Algorithm Performance*
- Explanation of how performance metrics guide decision-making in algorithm selection.
- Importance of confidence in algorithms and adjusting volume based on their reliability.
- Reference to the famous professor Andrew Ng's ML course and its significance for learners at different levels.
08:46 🌐 *Importance of Data Preprocessing*
- Introduction to the significance of data preprocessing in machine learning.
- Explanation of how major components like handling missing values, converting data types, and standardization contribute to data quality.
- Emphasis on the role of data preprocessing in improving the accuracy of machine learning models, using cancer detection as an example.
09:26 🧹 *Techniques in Data Preprocessing*
- Overview of techniques involved in data preprocessing, including handling missing values and converting string values to numbers.
- Importance of standardization, categorizing, and feature scaling in the preprocessing stage.
- Significance of gaining practical knowledge in data preprocessing for effective machine learning projects.
10:09 🛠️ *Advanced Data Preprocessing Techniques*
- Introduction to more advanced data preprocessing techniques, such as handling categorical values, feature engineering, and feature scaling.
- Explanation of the importance of understanding feature scaling and feature engineering for machine learning.
- Emphasis on the role of these techniques in preparing data for ML libraries like Tensorflow, making complex projects easier.
11:07 📚 *Leveraging ML Libraries for Simplified Projects*
- Discussion on using ML libraries, focusing on Google's TensorFlow.
- Reference to the abundance of pre-built models within libraries and their application in diverse projects.
- Encouragement to explore and utilize available ML libraries to simplify and enhance the machine learning project creation process.
11:19 📊 *Exploring Machine Learning Resources*
- Introduction to libraries like NetPlotLib for visualizing data in machine learning algorithms.
- Mention of Google's TensorFlow library and the wealth of deep learning resources available within it.
- Reference to the importance of exploring and utilizing available libraries for effective machine learning.
12:00 🧠 *Understanding Qualifications in Machine Learning*
- Discussion on qualifications and specializations in machine learning, drawing an analogy with medical studies.
- Introduction to the qualification path in machine learning, highlighting the importance of understanding neural networks.
- Reference to advanced topics and resources available within the field, emphasizing the depth of knowledge required.
12:41 🌐 *Learning Platforms and Datasets*
- Recommendation of different websites and platforms for learning machine learning, including available datasets.
- Highlighting the availability of comprehensive resources on specific websites and providing a reference link.
- Encouragement to practice and participate in contests on platforms to gain practical experience.
13:23 🚀 *Building Projects and Research Opportunities*
- Guidance on progressing from learning to building innovative projects and potential startup ideas.
- Suggestion to explore research opportunities, referencing organizations like DARPA.
- Introduction to applying for research programs, indicating options within institutes and organizations.
14:05 🎓 *Connecting with Research Students in IT*
- Encouragement to connect with research students in the IT branch of science.
- Suggestion to visit college campuses, showcase machine learning projects, and engage with students.
- Emphasis on building a network and collaborating on research projects with students who have expertise in machine learning.
14:33 🧠 *Importance of Learning Essential Algorithms*
- Highlighting the significance of learning essential algorithms for a strong foundation in machine learning.
- Reference to crucial topics that are essential for mastering machine learning.
- Providing links to important resources and algorithms for continuous learning and improvement.
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👉👉Apni didi toh jhakas che😉😉
Didi, please make a video on cloud computing and the resources from where we can learn cloud computing.. Plezz 🙏🙏
Okay Krishana
@@ApnaCollegeOfficial Thank You didi
@@krishanapaswan4239 y didi nhi Aman bhai ne jwab diya h ☺️
@@AnkitKumar-nx2tq how u know???🤔🤔
@@omgor2806 q ki channel aman bhai ka h,didi to job kar rhi h 🤓,so jisaka channel hota h vhi jwab deta h, password usake pas hi hote hn ☺️...
Kya bhai y b nhi pta🤓
Sb aman bhai hi krate hn, unke khane pe hi to y wo topic pdaynge....
Terrific video. Dil se thank you. Aap log boht acha kaam kar rahe hain
Much needed video, Thank you "Microsoft"!!
😂
A line by aman bhaiya I have edited it somehow😁 "Yaar yeh didi mtlb yeh didi toh chah h na " 😁
Mst btaya didi mujhe blockchain developing m jaana h and really appreciate you
Your's explanation is awesome and impactive, if possible plz make another vedio which will contain the approaches and goal towards "artificial intelligence"..
01:53 Machine learning is the combination of data and algorithms used in various technologies like Amazon, Google Assistant, etc.
03:46 Define your goal before learning machine learning
05:39 To learn machine learning, first, understand basics math, then learn Python and its libraries.
07:32 Python basics and important algorithms of machine learning
09:25 Algorithm selection based on accuracy is important in cancer detection
11:18 Data preprocessing is crucial for machine learning algorithms
13:11 Skykit learn, Matplotlib, and Tensorflow are important resources for machine learning and deep learning.
14:59 Explore opportunities in machine learning and advance your career.
Please make one more video based on how to approach for an interview where there is demand of machine learning and how to apply for internships as well in this field :)
Hi Bros and sis 😊 , I teach with free study material + practical concept + best handwtritten notes 😋+maths shortricks+ + JEE and NEET preparation + coding , and many more.
[ According to me once you should visit if anything is missing then comment their I will improve that ]👍
Superb Information Didi...
Thankyou...
This video is 🔥🔥
Thank you so much! This video should be on trending page 🤩
I LOVE YOU MERI JAAN BATAO KAB MILANA AAGA AAP MARA C
Thank you so much Ma’am for using Black background. It’s so helpful to learn. 👍
Very well explained.. thank you 🙏🏻
Didi toh kill kar rahi hai 🔥🔥🔥🔥🔥🔥🔥lots of love to Aman datarwal team❤️🔥
Thanks didi for this and can you pls teach us more about block chain and AI pls...and thanks to aman bhaiya and team apni kaksha
Thank you very much Didi for sharing this great knowledge 👌👌👍👍🌟🌟⭐🥀🌹🥀🌹💐💐💐
Please make a video on Roadmap to ARTIFICIAL INTELLIGENCE............PLZ PLZ PLZ PLZ PLZ PLZ PLZ....
Respect from Pakistan. Zabardast
Its always difficult to find resources in ML which includes maths along with its coding part.... I didn't get satisfactory course till now (its always like I missed something)... hoping this might help.🙂
Literally in this Videos Tones of Knowledge I Loved it!❤ *Microsoft Wali Didi ki Jai!*🔥
For machine learning it's necessary to learn maths behind algorithms to tune hyperparameters for getting good accuracy
Didi har jgah gyan nai pela jata ki maths krne ki zrurat nai🙂🙂
Listen first with ur ears open bro. She said about the goals related to product or algo. It is clear from her statements that heavy maths is needed for algos..
Literally video k starting k section me hi bola hai maths bohot jaruri.
Ab smj aaya sara kuch thank you so much 👏👏
Didi, I need a video on how to find projects, please can you make one
Do we need to register somewhere to make a project ???
She's a very good guide✨💕🌸
Never thought I'd go for ML but seeing this I just want to thank you guys for making this roadmap. You are guys are literal gods. Cheers
Really Informative talk...
Didi please give us some insight on MLOps and its scope.. honestly love this channel 👍
Machine Learning is the Future 🔥🔥🎉
Loving this series!
Great efforts and great guidance ! really so helpful I found what I expected. Thanks a lot
Thanks, was waiting for this one.
wah
back to back videos...
Mauj karde bete mauj karde