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Category: "Machine Learning"

Machine Learning

  1. 解剖深度学习原理
    解剖深度学习原理
    从0实现深度学习库
    hwdong

    市面上的深度学习书要么晦涩难懂,要么是平台使用说明书,只讲理论缺少实现或者只有编程缺少原理讲解,都很难让人理解深度学习的基本原理,本书采用理论讲解与代码实现的方式深入浅出地剖析了深度学习的技术原理和实现细节,教会读者如何从零编写一个深度学习库。内容包含了:梯度下降法、回归学习、前馈神经网络、卷积神经网络、循环神经网络、生成网络。

  2. What Just Happened: Descriptive Statistics
    What Just Happened: Descriptive Statistics
    An Explorer’s Guide to Data
    Shefali Nayak

    The book explains the core concepts and terminologies of Descriptive Statistics using real-world examples. The book contains 17 practice problems, 2 quizzes, 36 graphical representations and numerous examples to enable effective learning and understanding of the concepts. Please check the bundle options with this book for better deals!

  3. Understanding Deep Learning
    Understanding Deep Learning
    Application in Rare Event Prediction
    Chitta Ranjan

    "It is like a voyage of discovery, seeking not for new territory but new knowledge. It should appeal to those with a good sense of adventure," Dr. Frederick Sanger. I hope every reader enjoys this voyage in deep learning and find their adventure.

  4. Self aware Robot´s
    Self aware Robot´s
    Adrian Vasile

    I write this book for all the people who believe that link between technology and humans can create a better world. I believe that fast advancement of the technology will help our planet to solve many problems in a more fast smart way that what human brain is capable to do.All this because of fast development of microprocessor architecture.

  5. Feature Selection in Machine Learning
    Feature Selection in Machine Learning
    Over 20 methods to select the most predictive features and build simpler, faster, and more reliable machine learning models.
    Soledad Galli, PhD

    Learn how to implement various feature selection methods in a few lines of code and train faster, simpler, and more reliable machine learning models. Using Python open-source libraries, you will learn how to find the most predictive features from your data through filter, wrapper, embedded, and additional feature selection methods.

  6. 5G Basics & Architecture

    This is a short manual to understand the 4th Industrial Revolution Technologies & 5G in very easy & understandable language.

  7. Behavior Analysis with Machine Learning and R
    Behavior Analysis with Machine Learning and R
    A Sensors and Data Driven Approach
    Enrique Garcia Ceja

    Learn how to leverage the power of machine learning and deep learning to analyze behavioral patterns from sensors data and electronic records. This book shows you how to explore, preprocess, encode, and visualize your data. Learn introductory machine learning concepts and how to train supervised and unsupervised models using R.

  8. Hiring Data Scientists and Machine Learning Engineers

    Hiring Data Scientists and Machine Learning Engineers is a concise, practical guide to help you hire the right people for your organization. The book will help you navigate the plethora of data science related roles and skills and help you create an effective hiring strategy to suit your organization's needs.

  9. Machine Learning Factory
    Machine Learning Factory
    From the Idea to the Continuous Maintenance of any Machine Learning Application
    Larysa Visengeriyeva
    No Description Available
  10. Leaving the Rat Race with Python
    Leaving the Rat Race with Python
    An Insider's Guide to Freelance Developing
    Finxter and Lukas Rieger

    Is There a Six-Figure Freelance Developer in You?Leaving the Rat Race with Python shows you how to nurture, grow, and harness your work-from-home coding business online --- and live the good life!It's an insider's guide to freelance developing. Start your new thriving coding business now!

  11. Data Science Workflow for Beginners
    Data Science Workflow for Beginners
    Start your Data Science Journey into a Successful High Paying Career
    A.J. García

    This book takes you on an exclusive tour of Data Science, discover the workflow successful data scientists are following and download 26 datasets to start your journey right away after following the 3 data visuzalization projects on the book.

  12. Machine Learning: Theory and Implementation with Python
    No Description Available
  13. L’apprentissage automatique dans la vraie vie
    L’apprentissage automatique dans la vraie vie
    Petit guide pour la mise en production
    Nastasia Saby

    Un modèle de machine learning aussi puissant soit-il n’a aucune valeur s’il n’est pas en production. Le temps où l’apprentissage automatique était magique est dépassé. Ce qu’on veut aujourd’hui, ce sont des modèles en production qui apportent une plus-value. Ce livre est un guide pour mettre en production des modèles de machine learning.

  14. Clean Machine Learning Code

    Isn't it weird that ML software is super important, yet crazy fragile? If ML software is valuable but so unstable, how come data scientists and ML engineers are rarely trained on the basics of building profitable software systems? What to do about it?

  15. تعلم من خلال التطبيق: خوارزميات تعلم الآلة
    تعلم من خلال التطبيق: خوارزميات تعلم الآلة
    جميع الخوارزميات تم تطبيقها من خلال لغة بايثون
    د. إياد أبودوش

    هل تريد تعلم خوارزميات تعلم الالة بشكل عملي واضح وتطبيقي. في هذا الكتاب ستجد مرجع لخوارزميات تعلم الآلة مع أمثلة تطبيقية بلغة بايثون بلغة واضحة وسهلة الفهم