Hands-On Machine Learning | Inside The Book

[@pyr5881]

As a CS Ph.D. student with 2 top conference papers published, I am sure it's the best book for deep learning in the world. Even it's a hands-on book, it still has some maths that help readers to understand the models.

[@danielniels22]

i'm sorry, but it's a hands-on book. Don't high degree people like you tend to be more theoretical ? I mean, the maths of ML/AI is crazy, do you really recommend hands-on book like this? I'm kind of tired and bored by learning the maths of each ML/AI algorithm before quickly jump into the module (sklearn) instead. i'm very confused, how people out there do their ML/AI/DataScience job peacefully with just that practical experience, like just importing module, and some trial & error, change this and change that... I'm pretty sure most of this people doesn't fully understand the math. OMG i mean, how do they survive 😭😭😭😭

[@pyr5881]

@@danielniels22 Deep learning does not require much math knowledge. For CS PhD students, ML math is easy as they learned the foundation of ML theory. Also depending on the research, PhD students or PhDs can avoid research on the theory of machine learning. If they need, they just need to read the specific theories they need either from books or papers. Spending too much time to learn all machine learning algorithms without any research production is wasting time.

[@danielniels22]

@@pyr5881 so is it okay just to use the existing library/frameworks like TensorFlow, Keras, sklearn, etc? I don't know how does on the field feel like, do ML Engineers in companies understand the math? It is cool to see AI Documentaries like from the KZbin series "The Age of A.I.", i'm not sure if they build those cutting-edge AI without understanding the math deeply and just using the libraries out there

[@pyr5881]

@@danielniels22 I suggest you read some top conference papers, such as CVPR papers, in deep learning to know what current deep learning researchers are doing.

[@DataLinkz]

I actually have that same book and let me tell you the math is not easy you’ll have to learn the formulas but it’s totally doable

[@hardikvegad3508]

Solutions to these exercises are available in appendix A. Where can i find this Appendix A for hands on machine learning with scikit-learn and tensorflow 2

[@ragnarstefansson2841]

The solutions to all the exercises are near the end of the book , page 719 in the paperback version of the book.

[@muchharbharat7073]

Is this book helpful for building large language model I mean there are some concepts or discussions on that ¿

[@ぶらえんぴん]

Can you introduce some book about pytorch?

[@AnandSinghVentures]

Is this book for advanced Machine learning?

[@ramonpaolomaran2253]

i want know too

[@bakor-org]

Not really, its start from the basics