SC - 1354 | Genetic Algorithms with Python

Clinton Sheppard

Get a hands-on introduction to machine learning with genetic algorithms using Python. Step-by-step tutorials build your skills from Hello World! to optimizing one genetic algorithm with another, and finally genetic programming; thus preparing you to apply genetic algorithms to problems in your own field of expertise.

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SC - 1348 | Data Analysis From Scratch With Python: Beginner Guide using Python, Pandas, NumPy, Scikit-Learn, IPython, TensorFlow and Matplotlib

Peters Morgan

Are you thinking of becoming a data analyst using Python? If you are looking for a complete guide to data analysis using Python language and its library that will help you to become an effective data scientist, 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.

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SC - 1336 | Practical Video Game Bots: Automating Game Processes using C++, Python, and AutoIt

Ilya Shpigor

Develop and use bots in video gaming to automate game processes and see possible ways to avoid this kind of automation. This book explains how bots can be very helpful in games such as multiplayer online games, both for training your character and for automating repetitious game processes in order to start a competition with human opponents much faster.

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SC - 1334 | Python, Pygame, and Raspberry Pi Game Development

Sloan Kelly

Expand your basic knowledge of Python and use PyGame to create fast-paced video games with great graphics and sounds. This second edition shows how you can integrate electronic components with your games using the build-in general purpose input/output (GPIO) pins and some Python code to create two new games.

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SC - 1333 | Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning

Benjamin Bengfort, Tony Ojeda, Rebecca Bilbro

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning.

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SC - 1332 | Python Data Analytics: With Pandas, NumPy, and Matplotlib

Fabio Nelli

Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn.

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SC - 1329 | Practical Computer Vision Applications Using Deep Learning with CNNs: With Detailed Examples in Python Using TensorFlow and Kivy

Ahmed Fawzy Gad

Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial neural networks (ANNs), building one from scratch in Python, before optimizing it using genetic algorithms.

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SC - 1323 | Neural Networks A Visual Introduction for Beginners by Michael Taylor

Michael Taylor

A step-by-step visual journey through the mathematics of neural networks, and making your own using Python and Tensorflow.

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SC - 1322 | Thoughtful Machine Learning with Python: A Test-Driven Approach

Matthew Kirk

Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext.

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SC - 1321 | Building Chatbots with Python: Using Natural Language Processing and Machine Learning

Sumit Raj

Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight into natural language processing with the natural language toolkit (NLTK) for building a custom language processing platform for your chatbot. With this foundation, you will take a look at different natural language processing techniques so that you can choose the right one for you.

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SC - 1320 | Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning

Chris Albon

This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics.

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SC - 1312 | Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python

Akshay Kulkarni, Adarsha Shivananda

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.

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SC - 1307 | Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python

Jojo John Moolayil

Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.

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SC - 1283 | Classic Computer Science Problems in Python

David Kopec

Classic Computer Science Problems in Python deepens your knowledge of problem-solving techniques from the realm of computer science by challenging you with time-tested scenarios, exercises, and algorithms. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your "new" problems!

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