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Mastering Machine Learning with Python in Six Steps
  • Language: en
  • Pages: 469

Mastering Machine Learning with Python in Six Steps

  • Type: Book
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  • Published: 2019-10-01
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  • Publisher: Apress

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 impleme...

Mastering Machine Learning with Python in Six Steps
  • Language: en
  • Pages: 374

Mastering Machine Learning with Python in Six Steps

  • Type: Book
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  • Published: 2017-06-05
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  • Publisher: Apress

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 Learning with Python in Six Steps presents each topic in two parts: theoretical concepts and practical implementation using suitable Python packages. You’ll learn the fundamentals of Python programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as feature dimension reduction, regression, time series fo...

Pro Machine Learning Algorithms
  • Language: en
  • Pages: 379

Pro Machine Learning Algorithms

  • Type: Book
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  • Published: 2018-06-30
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  • Publisher: Apress

Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so that you get a practical understanding of all the levers that can be tuned in a model, before implementing the models in Python/R. You will cover all the major algorithms: supervised and unsupervised learning, which include linear/logistic regression; k-means clustering; PCA; recommender system; decision tree; random forest; GBM; and neural networks. You will also be expos...

Pro Deep Learning with TensorFlow
  • Language: en
  • Pages: 412

Pro Deep Learning with TensorFlow

  • Type: Book
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  • Published: 2017-12-06
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  • Publisher: Apress

Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with TensorFlow provides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful deep learning solutions. This book will allow you to get up to speed quickly using TensorFlow and to optimize different deep learning architectures. All of the practical aspects of deep learning that are relevant in any industry are emphasized in this book. You will be able to use the prototypes demonstrated to build new deep learning applicat...

Learn Keras for Deep Neural Networks
  • Language: en
  • Pages: 192

Learn Keras for Deep Neural Networks

  • Type: Book
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  • Published: 2018-12-07
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  • Publisher: Apress

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. The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can b...

Intelligent Projects Using Python
  • Language: en
  • Pages: 332

Intelligent Projects Using Python

Implement machine learning and deep learning methodologies to build smart, cognitive AI projects using Python Key FeaturesA go-to guide to help you master AI algorithms and concepts8 real-world projects tackling different challenges in healthcare, e-commerce, and surveillanceUse TensorFlow, Keras, and other Python libraries to implement smart AI applicationsBook Description This book will be a perfect companion if you want to build insightful projects from leading AI domains using Python. The book covers detailed implementation of projects from all the core disciplines of AI. We start by covering the basics of how to create smart systems using machine learning and deep learning techniques. Y...

Machine Learning Applications Using Python
  • Language: en
  • Pages: 384

Machine Learning Applications Using Python

  • Type: Book
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  • Published: 2018-12-12
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  • Publisher: Apress

Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you’ll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only discover how machine learning is used in finance, healthcare, and retail, but also work through practical case studies where machine learning has been implemented. Machine Learning Applications Using Python is divided into three sections, one for each of the domains (healthcare, finance, and retail). Each section starts with an overview of machine learning and key technological advancemen...

Proceedings of Third International Conference in Mechanical and Energy Technology
  • Language: en
  • Pages: 537
Manorama Year Book
  • Language: en
  • Pages: 816

Manorama Year Book

  • Type: Book
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  • Published: 1999
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  • Publisher: Unknown

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Fundamentals of Data Science
  • Language: en
  • Pages: 297

Fundamentals of Data Science

  • Type: Book
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  • Published: 2021-09-26
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  • Publisher: CRC Press

Fundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science. Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect, aggregate, process, and gain insights from massive datasets. This book offers all the processes, methodologies, various steps like data acquisition, pre-process, mining, prediction, and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processes Readers wi...