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Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python
Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras

Key Features

  • Implement machine learning algorithms to build, train, and validate algorithmic models
  • Create your own algorithmic design process to apply...
Database Benchmarking and Stress Testing: An Evidence-Based Approach to Decisions on Architecture and Technology
Database Benchmarking and Stress Testing: An Evidence-Based Approach to Decisions on Architecture and Technology
Provide evidence-based answers that can be measured and relied upon by your business. Database administrators will be able to make sound architectural decisions in a fast-changing landscape of virtualized servers and container-based solutions based on the empirical method presented in this book for answering “what if”...
Open Source Intelligence Methods and Tools: A Practical Guide to Online Intelligence
Open Source Intelligence Methods and Tools: A Practical Guide to Online Intelligence
Apply Open Source Intelligence (OSINT) techniques, methods, and tools to acquire information from publicly available online sources to support your intelligence analysis. Use the harvested data in different scenarios such as financial, crime, and terrorism investigations as well as performing business competition analysis and acquiring...
TensorFlow Machine Learning Cookbook: Over 60 recipes to build intelligent machine learning systems with the power of Python, 2nd Edition
TensorFlow Machine Learning Cookbook: Over 60 recipes to build intelligent machine learning systems with the power of Python, 2nd Edition

Skip the theory and get the most out of Tensorflow to build production-ready machine learning models

Key Features

  • Exploit the features of Tensorflow to build and deploy machine learning models
  • Train neural networks to tackle real-world problems in Computer Vision and...
Hands-On Markov Models with Python: Implement probabilistic models for learning complex data sequences using the Python ecosystem
Hands-On Markov Models with Python: Implement probabilistic models for learning complex data sequences using the Python ecosystem

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...
Python Reinforcement Learning Projects: Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow
Python Reinforcement Learning Projects: Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow

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...
Applied Deep Learning with Python: Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions
Applied Deep Learning with Python: Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions

A hands-on guide to deep learning that's filled with intuitive explanations and engaging practical examples

Key Features

  • Designed to iteratively develop the skills of Python users who don't have a data science background
  • Covers the key foundational concepts...
Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python
Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python

Develop real-world applications powered by the latest advances in intelligent systems

Key Features

  • Gain real-world contextualization using deep learning problems concerning research and application
  • Get to know the best practices to improve and optimize your machine...
Beginning Java Data Structures and Algorithms: Sharpen your problem solving skills by learning core computer science concepts in a pain-free manner
Beginning Java Data Structures and Algorithms: Sharpen your problem solving skills by learning core computer science concepts in a pain-free manner

Though your application serves its purpose, it might not be a high performer. Learn techniques to accurately predict code efficiency, easily dismiss inefficient solutions, and improve the performance of your application.

Key Features

  • Explains in detail different algorithms and data...
Beginning Application Development with TensorFlow and Keras: Learn to design, develop, train, and deploy TensorFlow and Keras models as real-world applications
Beginning Application Development with TensorFlow and Keras: Learn to design, develop, train, and deploy TensorFlow and Keras models as real-world applications

You need much more than imagination to predict earthquakes and detect brain cancer cells. Become an expert in designing and deploying TensorFlow and Keras models, and generate insightful predictions with the power of deep learning.

Key Features

  • Cover the basics of neural networks and...
Getting Started with Python for the Internet of Things: Leverage the full potential of Python to prototype and build IoT projects using the Raspberry Pi
Getting Started with Python for the Internet of Things: Leverage the full potential of Python to prototype and build IoT projects using the Raspberry Pi

Build clever, collaborative, and powerful automation systems with the Raspberry Pi and Python.

Key Features

  • Create your own Pi-Rover or Pi-Hexipod robots
  • Develop practical applications in Python using Raspberry Pi
  • Build your own Jarvis, a highly advanced...
R Deep Learning Essentials
R Deep Learning Essentials

Key Features

  • Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
  • Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
  • Build models relating to neural...
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