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Showing: 21-30 results of 8817

Create AI applications in Python and lay the foundations for your career in data science Key Features Practical examples that explain key machine learning algorithms Explore neural networks in detail with interesting examples Master core AI concepts with engaging activities Book Description Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and... more...

Insightful projects to master deep learning and neural network architectures using Python and Keras Key Features Explore deep learning across computer vision, natural language processing (NLP), and image processing Discover best practices for the training of deep neural networks and their deployment Access popular deep learning models as well as widely used neural network architectures Book Description Deep... more...

This book Includes 3 Manuscripts in 1 book: - Python For Beginners: A Crash Course Guide To Learn Python in 1 Week - Python 3 Guide: A Beginner Crash Course Guide to Learn Python 3 in 1 Week - Learn Java: A Crash Course Guide to Learn Java in 1 Week Python For Beginners: A Crash Course Guide To Learn Python in 1 Week Here what you'll learn after downloading this Python for Beginners book: ✓Introduction✓Chapter 1: Python: A... more...

Python For Beginners: A Crash Course Guide To Learn Python in 1 Week Here what you'll learn after downloading this Python for Beginners book: ✓Introduction✓Chapter 1: Python: A Comprehensive Background ✓Chapter 2: How to Download and Install Python✓Chapter 3: Python Glossary✓Chapter 4: Interacting with Python✓Chapter 5: Using Turtle for a Simple Drawing✓Chapter 6: Variables✓Chapter 7: Loops✓Chapter 8: Native Python... more...

This  book provides a general and comprehensible overview of   imbalanced learning.  It contains a formal description of a problem, and focuses on its main features, and the most relevant proposed solutions. Additionally, it considers the different scenarios in Data Science for which the imbalanced classification can create a real challenge.  This book stresses the gap with standard classification... more...


Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda Key Features Use Anaconda to find solutions for clustering, classification, and linear regression Analyze your data efficiently with the most powerful data science stack Use the Anaconda cloud to store, share, and discover projects and libraries Book Description Anaconda is an open source platform that... more...

Implement state-of-the-art deep reinforcement learning algorithms using Python and its powerful libraries Key Features Implement Q-learning and Markov models with Python and OpenAI Explore the power of TensorFlow to build self-learning models Eight AI projects to gain confidence in building self-trained applications Book Description Reinforcement learning is one of the most exciting and rapidly growing fields in... more...

A practical guide to mastering reinforcement learning algorithms using Keras Key Features Build projects across robotics, gaming, and finance fields, putting reinforcement learning (RL) into action Get to grips with Keras and practice on real-world unstructured datasets Uncover advanced deep learning algorithms such as Monte Carlo, Markov Decision, and Q-learning Book Description Reinforcement learning has... more...

Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem Key Features Build deep learning models with transfer learning principles in Python implement transfer learning to solve real-world research problems Perform complex operations such as image captioning neural style transfer Book Description Transfer learning is a machine learning... more...

Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearn Key Features Build a variety of Hidden Markov Models (HMM) Create and apply models to any sequence of data to analyze, predict, and extract valuable insights Use natural language processing (NLP) techniques and 2D-HMM model for image segmentation Book Description Hidden Markov Model (HMM) is a... more...