This book is written to provide a strong foundation in machine learning using Python libraries by providing real-life case studies and examples. It covers topics such as foundations of machine learning, introduction to Python, descriptive analytics and predictive analytics. Advanced machine learning concepts such as decision tree learning, random forest, boosting, recommended systems, and text analytics are covered. The book takes a balanced approach between theoretical understanding and practical applications. All the topics include real-world examples and provide step-by-step approach on how to explore, build, evaluate, and optimize machine learning models.
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Machine Learning using Python
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Prashanthi Parepally –
I am currently in an AIML course. I got this book midway and loved reading it. Learnt so much introductory material that was not covered in the class. I am new to python, so where it started was perfect for me. Third chapter was a little dry but chapter 2,4 and time series ones were what I read so far and already completed kaggle project just based on what I learnt in these. Highly recommend for starters. Would like to pass on thanks to the author!!
Abhilash Tyagi –
I have just started reading it and read only 3 chapters of it, but can’t resist myself from writing the review. I have been searching for the right book to start with the data science along with the online course and this book fits right in. The examples, way of writing the book are just excellent. Although this book is not comprehensive ( i believe no book on ML is) but it starts with the basic and clear concepts very well.
Kudos to the authors.
Mayank –
Book has a wiley-india link where you can download codes and datasets used in the examples throughout the book.
Running those codes in your own jupyter notebook gives good sense of what is happening(can add these in your github). Probability & stats part is not explained well, has to refer some other book for that.
A S –
This book is one of the best for learning Python for Machine learning for beginners, especially those who do not come from coding background. After going through several courses on udacity, datacamp, yet failing screening Python coding rounds for Data Science positions, I realised that the subject matter coverage in this book is the most systematic and comprehensive.