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Python Machine Learning By Example - Build intelligent systems using Python, TensorFlow 2, PyTorch, and scikit-learn, 3rd Edition (Paperback, 3rd Revised edition)
Loot Price: R1,084
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Python Machine Learning By Example - Build intelligent systems using Python, TensorFlow 2, PyTorch, and scikit-learn, 3rd Edition (Paperback, 3rd Revised edition)
Expected to ship within 10 - 15 working days
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A comprehensive guide to get you up to speed with the latest
developments of practical machine learning with Python and upgrade
your understanding of machine learning (ML) algorithms and
techniques Key Features Dive into machine learning algorithms to
solve the complex challenges faced by data scientists today Explore
cutting edge content reflecting deep learning and reinforcement
learning developments Use updated Python libraries such as
TensorFlow, PyTorch, and scikit-learn to track machine learning
projects end-to-end Book DescriptionPython Machine Learning By
Example, Third Edition serves as a comprehensive gateway into the
world of machine learning (ML). With six new chapters, on topics
including movie recommendation engine development with Naive Bayes,
recognizing faces with support vector machine, predicting stock
prices with artificial neural networks, categorizing images of
clothing with convolutional neural networks, predicting with
sequences using recurring neural networks, and leveraging
reinforcement learning for making decisions, the book has been
considerably updated for the latest enterprise requirements. At the
same time, this book provides actionable insights on the key
fundamentals of ML with Python programming. Hayden applies his
expertise to demonstrate implementations of algorithms in Python,
both from scratch and with libraries. Each chapter walks through an
industry-adopted application. With the help of realistic examples,
you will gain an understanding of the mechanics of ML techniques in
areas such as exploratory data analysis, feature engineering,
classification, regression, clustering, and NLP. By the end of this
ML Python book, you will have gained a broad picture of the ML
ecosystem and will be well-versed in the best practices of applying
ML techniques to solve problems. What you will learn Understand the
important concepts in ML and data science Use Python to explore the
world of data mining and analytics Scale up model training using
varied data complexities with Apache Spark Delve deep into text
analysis and NLP using Python libraries such NLTK and Gensim Select
and build an ML model and evaluate and optimize its performance
Implement ML algorithms from scratch in Python, TensorFlow 2,
PyTorch, and scikit-learn Who this book is forIf you're a machine
learning enthusiast, data analyst, or data engineer highly
passionate about machine learning and want to begin working on
machine learning assignments, this book is for you. Prior knowledge
of Python coding is assumed and basic familiarity with statistical
concepts will be beneficial, although this is not necessary.
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