Underrated channel. Superb teaching. No channel comes even close to how eloquently he is educating. Can we expect complete courses on machine learning, deep learning and new age ai trends like agi, llm, etc? Can You bring a complete course on developing end-end ai based projects? Forgive me as I asked for so many things, it's because I have never experienced an educator like You Sir.
Thank you so much for your kind words! You made my day! Sure, I am working on more videos that will help you to understand end to end implementation of AI projects in the industry. GenAI will follow shortly.
🫡Hats off Sir.. You're the most valuable I've ever seen in my life.. The concepts explanation from scratch is god damn... It's precise & not deviating the content.. I'm very much impressed on your sharable knowledge in Machine learning ❤️❤️ Keep up the great work Sir.. Love from India 🫶
Sure, look at this video to understand the difference and overlap between ML and DS! ua-cam.com/video/-89CnfPCMtQ/v-deo.html and no I am not indiainpixels! :)
Just clicked on your video thinking another clikbait video . But I have to admit you proved me wrong. Hoping for more valuable content like this from you in future.
Very good explanation. But I would say one thing is missing here. There is a subtle difference between a data scientist and a machine learning engineer. Data scientists mostly deal with the business data and ML engineers work in the process of building a product based on machine learning. It is true that there are lot of similarities between the task of a data scientist and a machine learning engineer. A data scientist can also create products and ML engineers can also work in the business domain. But still these are just possibilities. These are not specifications. Beginners often feel so much confused between these two things. And many of them started to think that two are similar. In current job market, the requirements of a data scientist and ML engineer are quite different. ML engineers need lot of software engineering skills along with machine learning skills. ML engineers are just a special kind of software engineers.
Your observation is bang on! A data scientist holds knowledge regarding the domain along with ML algorithms and their applications. They need not be domain experts but should understand the basics of the industry like CPG, Healthcare, Insurance etc. depending on whatever project they are working on. Typically, that happens when you have gained some experience working as a ML engineer under the guidance of senior Data Scientists in the project. This is actually a separate topic in itself and I have covered it in the below video! ua-cam.com/video/-89CnfPCMtQ/v-deo.htmlsi=KoxCS11MUIImgwIZ Thank you for the feedback! Cheers!
![Lp. Сердце Вселенной #60 РОЖДЕНИЕ ЛОЛОЛОШКИ [Финал] • Майнкрафт](http://i.ytimg.com/vi/YoR0pAV9FVQ/mqdefault.jpg)
Underrated channel. Superb teaching. No channel comes even close to how eloquently he is educating.
Can we expect complete courses on machine learning, deep learning and new age ai trends like agi, llm, etc?
Can You bring a complete course on developing end-end ai based projects?
Forgive me as I asked for so many things, it's because I have never experienced an educator like You Sir.
Thank you so much for your kind words! You made my day!
Sure, I am working on more videos that will help you to understand end to end implementation of AI projects in the industry. GenAI will follow shortly.
@@thinking_neuron 😀 warm welcome Sir. Ultra thanks and your continuing efforts are incredible!
I am glad you are posting again, your videos deserve much more.
Thank you for the encouragement! :)
You deserve more views, thankyou bro.
Thank you Guru! Keep sharing with friends! 😃
🫡Hats off Sir.. You're the most valuable I've ever seen in my life.. The concepts explanation from scratch is god damn... It's precise & not deviating the content.. I'm very much impressed on your sharable knowledge in Machine learning ❤️❤️ Keep up the great work Sir..
Love from India 🫶
Wow! I am very happy and glad to see that these videos are helping you.
Thank you so much for your kind words, this encourages me a lot!
Cheers! 😊
grate work
Thank you Dhanush!
Nice work
Thank you for the appreciation!
nice to see you back.
great video
Thank you Ayush!
nice one
Thank you! 😊
I subscribed
Thank you
Can we have a series of DS or ML roadmap? I'm confuse bcz they overlap.
Wait r u @indiainpixels ?
Sure, look at this video to understand the difference and overlap between ML and DS!
ua-cam.com/video/-89CnfPCMtQ/v-deo.html
and no I am not indiainpixels! :)
Just clicked on your video thinking another clikbait video . But I have to admit you proved me wrong. Hoping for more valuable content like this from you in future.
I am glad you liked this one! Thank you for taking time to provide feedback! Sure, I will work harder and create more useful videos. Cheers!
😍
Very good explanation. But I would say one thing is missing here. There is a subtle difference between a data scientist and a machine learning engineer. Data scientists mostly deal with the business data and ML engineers work in the process of building a product based on machine learning. It is true that there are lot of similarities between the task of a data scientist and a machine learning engineer. A data scientist can also create products and ML engineers can also work in the business domain. But still these are just possibilities. These are not specifications. Beginners often feel so much confused between these two things. And many of them started to think that two are similar. In current job market, the requirements of a data scientist and ML engineer are quite different. ML engineers need lot of software engineering skills along with machine learning skills. ML engineers are just a special kind of software engineers.
Your observation is bang on!
A data scientist holds knowledge regarding the domain along with ML algorithms and their applications. They need not be domain experts but should understand the basics of the industry like CPG, Healthcare, Insurance etc. depending on whatever project they are working on.
Typically, that happens when you have gained some experience working as a ML engineer under the guidance of senior Data Scientists in the project.
This is actually a separate topic in itself and I have covered it in the below video!
ua-cam.com/video/-89CnfPCMtQ/v-deo.htmlsi=KoxCS11MUIImgwIZ
Thank you for the feedback!
Cheers!