Mastering Machine Learning With Python In Six Steps

Mastering Machine Learning with Python in Six Steps
Publisher Apress
Release Date
Category Computers
Total Pages 457
ISBN 9781484249475
Rating 4/5 from 21 reviews
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Explore fundamental to advanced Python 3 topics in six steps, all designed to make you a worthy practitioner. This updated version’s approach is based on the “six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away and presents each topic in two parts: theoretical concepts and practical implementation using suitable Python 3 packages. You’ll start with the fundamentals of Python 3 programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as exploratory analysis, feature dimension reduction, regressions, time series forecasting and their efficient implementation in Scikit-learn are covered as well. You’ll also learn commonly used model diagnostic and tuning techniques. These include optimal probability cutoff point for class creation, variance, bias, bagging, boosting, ensemble voting, grid search, random search, Bayesian optimization, and the noise reduction technique for IoT data. Finally, you’ll review advanced text mining techniques, recommender systems, neural networks, deep learning, reinforcement learning techniques and their implementation. All the code presented in the book will be available in the form of iPython notebooks to enable you to try out these examples and extend them to your advantage. What You'll Learn Understand machine learning development and frameworks Assess model diagnosis and tuning in machine learning Examine text mining, natuarl language processing (NLP), and recommender systems Review reinforcement learning and CNN Who This Book Is For Python developers, data engineers, and machine learning engineers looking to expand their knowledge or career into machine learning area.

Mastering Machine Learning with Python in Six Steps
  • Author : Manohar Swamynathan
  • Publisher : Apress
  • Release Date : 2019-10-01

Explore fundamental to advanced Python 3 topics in six steps, all designed to make you a worthy practitioner. This updated version’s approach is based on the “six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away and presents each topic in two

GET BOOK
Mastering Machine Learning with Python in Six Steps
  • Author : Manohar Swamynathan
  • Publisher : Apress
  • Release Date : 2019-10-02

Explore fundamental to advanced Python 3 topics in six steps, all designed to make you a worthy practitioner. This updated version’s approach is based on the “six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away and presents each topic in two

GET BOOK
Master Machine Learning Algorithms
  • Author : Jason Brownlee
  • Publisher : Machine Learning Mastery
  • Release Date : 2016-03-04

You must understand the algorithms to get good (and be recognized as being good) at machine learning. In this Ebook, finally cut through the math and learn exactly how machine learning algorithms work, then implement them from scratch, step-by-step.

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Mastering Machine Learning with Python in Six Steps
  • Author : Manohar Swamynathan
  • Publisher : Apress
  • Release Date : 2017-06-05

Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. This book’s approach is based on the “Six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine

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Machine Learning Mastery With Python
  • Author : Jason Brownlee
  • Publisher : Machine Learning Mastery
  • Release Date : 2016-04-08

The Python ecosystem with scikit-learn and pandas is required for operational machine learning. Python is the rising platform for professional machine learning because you can use the same code to explore different models in R&D then deploy it directly to production. In this Ebook, learn exactly how to get

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Practical Machine Learning with Python
  • Author : Dipanjan Sarkar,Raghav Bali,Tushar Sharma
  • Publisher : Apress
  • Release Date : 2017-12-20

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts,

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Mastering Machine Learning with scikit learn
  • Author : Gavin Hackeling
  • Publisher : Packt Publishing Ltd
  • Release Date : 2017-07-24

Use scikit-learn to apply machine learning to real-world problems About This Book Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks Learn how to build and evaluate performance of efficient models using scikit-learn Practical guide to master your basics and

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Deep Learning with PyTorch
  • Author : Luca Pietro Giovanni Antiga,Eli Stevens,Thomas Viehmann
  • Publisher : Simon and Schuster
  • Release Date : 2020-07-01

“We finally have the definitive treatise on PyTorch! It covers the basics and abstractions in great detail. I hope this book becomes your extended reference document.” —Soumith Chintala, co-creator of PyTorch Key Features Written by PyTorch’s creator and key contributors Develop deep learning models in a familiar Pythonic way

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Machine Learning with Python Cookbook
  • Author : Chris Albon
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2018-03-09

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

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Python for Probability  Statistics  and Machine Learning
  • Author : José Unpingco
  • Publisher : Springer
  • Release Date : 2019-06-29

This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working meaningful examples

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Mastering Machine Learning Algorithms
  • Author : Giuseppe Bonaccorso
  • Publisher : Packt Publishing Ltd
  • Release Date : 2018-05-25

Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and

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Natural Language Processing Recipes
  • Author : Akshay Kulkarni,Adarsha Shivananda
  • Publisher : Apress
  • Release Date : 2019-01-29

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. Natural Language Processing

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Machine Learning in Action
  • Author : Peter Harrington
  • Publisher : Simon and Schuster
  • Release Date : 2012-04-03

Summary Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization

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Pragmatic AI
  • Author : Noah Gift
  • Publisher : Addison-Wesley Professional
  • Release Date : 2018-07-12

Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background

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Python Machine Learning Case Studies
  • Author : Danish Haroon
  • Publisher : Apress
  • Release Date : 2017-10-27

Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal

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