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Chapter 1: An intuitive look at the fundamentals of deep learning based on practical applicationsChapter 2: A survey of the current state-of-the-art implementations of libraries, tools and packages for deep learning and the case for the Python ecosystemChapter 3: A detailed look at Keras [1], which is a high level framework for deep learning suitable for beginners to understand and experiment with deep learningChapter 4: A detailed look at Theano [2], which is a low level framework for implementing architectures and algorithms in deep learning from scratchChapter 5: A detailed look at Caffe [3], which is highly optimized framework for implementing some of the most popular deep learning architectures (mainly computer vision)Chapter 6: A brief introduction to GPUs and why they are a game changer for Deep LearningChapter 7: A brief introduction to Automatic DifferentiationChapter 8: A
Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz's popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It's an ideal way to begin, whether you're new to
Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects. If you've been curious about machine learning but didn't know where to start, this is the book you've been waiting for. Focusing on the subfield of machine
The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has
Chapter 1- Perceptrons- Introduction to Perceptrons- Working of a Perceptron- Program to understand the working of a PerceptronChapter 2: Neural Networks- Introduction to Neural Networks- Types of Neural Networks- How each neural network works- Program to understand the working of Neural
Learn PySparkChapter 1: Introduction to PySparkChapter 2: Data ProcessingChapter 3: Spark Structured StreamingChapter 4: AirflowChapter 5: Machine Learning Library (MLlib)Chapter 6: Supervised Machine LearningChapter 7: Unsupervised Machine LearningChapter 8: Deep Learning Using PySpark
An introduction to natural language processing with Python using spaCy, a leading Python natural language processing library. Natural Language Processing with Python and spaCy will show you how to create NLP applications like chatbots, text-condensing scripts, and order-processing tools quickly and
The Complete Beginner's Guide to Understanding and Building Machine Learning Systems with Python Machine Learning with Python for Everyone will help you master the processes, patterns, and strategies you need to build effective learning systems, even if you're an absolute beginner. If you can
Strojové učení zaznamenalo v posledních letech pozoruhodný pokrok a dospělo od téměř nepoužitelného rozpoznávání řeči a obrazu k téměř nadlidské přesnosti, od programů, které nedokázaly porazit jen trochu zkušenějšího hráče šachu, až k přemožitelům mistrů
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
In Math for Programmers you'll explore important mathematical concepts through hands-on coding. Summary To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these
Summary Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF,
A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math. Ever since computers began beating us at chess, they've been getting better at
A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides you through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or
Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective. Summary Learn Quantum Computing with Python and Q# demystifies quantum computing. Using Python and the new quantum programming language Q#, you'll build your own quantum simulator and apply quantum
Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular machine learning methods. This book serves as a practitioner's guide to the machine learning process and is meant to help the reader learn to apply the machine
Learn math by getting creative with code Use the Python programming language to transform learning high school-level math topics like algebra, geometry, trigonometry, and calculus In Hacking Math, teacher and programmer Peter Farrell shows you how to explore core math concepts deeper than ever
Program a graphical adventure game in this hands-on, beginner-friendly introduction to coding in the Python language. Launch into coding with Mission: Python, a space-themed guide to building a complete computer game in Python. You'll learn programming fundamentals like loops, strings, and lists as
Business users familiar with Base SAS programming can now learn Python by example. You will learn via examples that map SAS programming constructs and coding patterns into their Python equivalents. Your primary focus will be on pandas and data management issues related to analysis of data. It is
Chapter 1: Data Visualization with LeatherChapter Goal: Introduce readers to the data visualization with a simple library leatherNo of pages: 15Sub - Topics: 1. Introduction to leather2. Installation to leather3. Various types of graphs with leatherChapter 2: Introduction to the Scientific Python
A project-based approach to learning Python programming for beginners. Intriguing projects teach you how to tackle challenging problems with code. You've mastered the basics. Now you're ready to explore some of Python's more powerful tools. Real-World Python will show you how. Through a series of
The must-have companion guide to the Raspberry Pi UserGuide Raspberry Pi chose Python as its teaching language of choice toencourage a new generation of programmers to learn how to program.This approachable book serves as an ideal resource for anyonewanting to use Raspberry Pi to learn to program
The kid-friendly way to learning coding with Python Calling all wanna-be coders Experts point to Python as one of the best languages to start with when you're learning coding, and Python For Kids For Dummies makes it easier than ever. Packed with approachable, bite-sized projects that won't make
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. Featuring graphs and highlighted code examples throughout, the book