Hands-On Machine Learning with Scikit-Learn and TensorFlow

A series of Deep Learning breakthroughs have boosted the whole field of machine learning over the last decade Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data This practical book shows you how.By using concrete examples, minimal theory, and two production ready Python frameworks Scikit Learn and TensorFlow author Aur lien G ron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems You ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks If you have some programming experience and you re ready to code a machine learning project, this guide is for you.This hands on book shows you how to use Scikit Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details Read Hands-On Machine Learning with Scikit-Learn and TensorFlow Author Aurélien Géron – kino-fada.fr One of the best ML books out there Dives deep into the practical implementation of Sklearn and Tensorflow Also, dives deep enough into the math side of ML Read it from cover to cover Really worth it.The book contains a chapter that shows a basic flow for working with data problems The TF chapters are interesting but somehow short I would have likedon convolutional layers and RNN.The reinforcement learning chapter is very interesting.great introduction into machine learning for both developer and non developers authors suggests to just go through even if you don t understand math details main points are extraction of field expert knowledge is very important you should know which model will serve better for the given solution luckily lot of models are available already from other scientists training data is the most important part theyou have it the better so if you can you should accumulate as much data as great introduction into machine learning for both developer and non developers authors suggests to just go through even if you don t understand math details main points are extraction of field expert knowledge is very important you should know which model will serve better for the given solution luckily lot of models are available already from other scientists training da...This is the best book I ve read on machine learning It is well written and the examples are very good with real data sets.The first half is an introduction to machine learning and the second half explores deep learning It is a great book to read along an online course., Hands On Machine Learning with Scikit Learn TensorFlow Hands On Machine Learning,, , tensoflow Hands On Machine Learning , Hands On Machine Learning with Scikit Learn TensorFlow Hands On Machine Learning,, , tensoflow Hands On Machine Learning 1 .2 .3 .4 .5 .6 .7 .8...Here are what I expected from the book and it actually did achieve The intended way to use Scikit learn and TensorFlow Specifically, essential building components, the understanding of their capacities in modelling and how to extend a model systematically, from a software engineering s perspective.What I did not expect but happy to learn about A typical guideline of how to attack a machine learning problem An update of almost all well known models the first half is about Decision Tree, S Here are what I expected from the book and it actually did achieve The intended way to use Scikit learn and TensorFlow Specifically, essential building components, the understanding of their capacities in modelling and how to extend a model systematically, from a software engineering s perspective.What I did not expect but happy to learn about A typical guideline of how to attack a machine learning problem An update of almost all well known models the first half is about Decision Tree, SVM, etc whereas the...5 for the first half of the book, scikit learn 3 for the second half, Tensor Flow Nice examples with Jupyter notebooks Good mix of practical with theoretical The scikit learn section is a great reference, nice detailed explanation with good references for further reading to deepen your knowledge The tensor flow part is weaker as examples becomecomplex Chollet s book Deep Learning with Python, which uses Keras is much stronger, as the examples are easier to understand as Keras is a 5 for the first half of the book, scikit learn 3 for the second half, Tensor Flow Nice examples with Jupyter notebooks Good mix of practical with theoretical The scikit learn section is a great reference, nice detailed explanation with good references for further reading to deepen your knowledge The tensor flow part is weaker as examples becomecomplex Chollet s book Deep Learning with Python, which uses Keras is much stronger, as the examples are easier to understand as Keras is a sim...I like the first half of the book a lot It provides a big picture view of machine learning in general and some of the most commonly used algorithms, in a conceptual and easy to follow way The second half, not so much At least part of the blam...Okay, best technical book read this year award still three months to go though goes to this book Initially it feels a bit odd that the focus is first put on scikit learn and that tensorflow seems to be added as an afterthought but in the end it s really ...Fantastic book to connect the dots between theory, techniques, and technologies in the ML world The domain is moving fast, and this book together with the source code is to me a tremendous guide in the existing yet still growing m...

• English
• 06 October 2018
Aurélien Géron
• Kindle Edition
• 450 pages
• Aurélien Géron
• Hands-On Machine Learning with Scikit-Learn and TensorFlow