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Convolutional Neural Networks in Python_ Master Data Science and Machine Learning with Modern Deep Learning in Python, Theano, and TensorFlow (Machine Learning in Python)

This is the 3rd part in my Data Science and Machine Learning series on Deep Learning in Python. At this point, you already know a lot about neural networks and deep learning, including not just the basics like backpropagation, but how to improve it using modern techniques like momentum and adaptive learning rates. You've already written deep neural networks in Theano and TensorFlow, and you know how to run code using the GPU.

Natural Language Processing Recipes_ Unlocking Text Data with Machine Learning and Deep Learning using Python

Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identification, topic modeling, text summarization, text generation, entity extraction, and sentiment analysis. 

Machine Learning_ Step-by-Step Guide To Implement Machine Learning Algorithms with Python

This book is for anyone who would like to learn how to develop machine-learning systems. We will cover the most important concepts about machine learning algorithms, in both a  theoretical and a practical way, and we'll implement many machine-learning algorithms using the Scikit-learn library in the Python programming language.

Introduction to Machine Learning with Python

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.

Python for Data Analysis_ Data Wrangling with Pandas, NumPy, and IPython

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupiter in the process.

Data Analysis From Scratch With Python_ Beginner Guide using Python, Pandas, NumPy, Scikit-Learn, IPython, TensorFlow and Matplotlib

If you are looking for a complete guide to data analysis using Python language this book is for you. From AI Sciences Publisher Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. It will help you in preparing a solid foundation and learn any other high-level courses.

Learn Python in One Day and Learn It Well_ Python for Beginners with Hands-on Project. The only book you need to start coding in Python immediately

Have you always wanted to learn computer programming but are afraid it'll be too difficult for you? Or perhaps you know other programming languages but are interested in learning the Python language fast? This book is for you. You no longer have to waste your time and money learning Python from lengthy books, expensive online courses or complicated Python tutorials.

C - Notes for Professionals

This C Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow.

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