Leanpub Header

Skip to main content

Filters

Category: "Artificial Intelligence"

Artificial Intelligence

  1. Data Harmonization in the Key of C
    Data Harmonization in the Key of C
    (or How to Tune Your Data)
    Michaël Brands

    IF your data isn't contextual, connected, complete & controllable; you don't control your data, your talent, and the impact they can make; you don't know how to use data to manage the cycle of innovation in a global market; you're not in the Sweet Spot where this comes together in harmony... This is the book you didn't even know you needed

  2. 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.

  3. Learn Python Basics in Weekend
    Learn Python Basics in Weekend
    Learn Python Part I: Learn Python Programming Basics
    Hisham El-Amir

    This series will introduce you to the Python programming language. It’s aimed at beginning programmers, but even if you’ve written programs before and just want to add Python to your list of languages, Introducing Python will get you started.

  4. Does Your Brain Need You?
    Does Your Brain Need You?
    An Introduction to Neuroscience and Consciousness
    Clemens Lode

    Recently, researchers have found a theory that explains every aspect of conscious experience. This book explores this theory and introduces you to neuroscience and gives you instructions how to build a conscious machine.

  5. Network Analysis Made Simple
    Network Analysis Made Simple
    An introduction to network analysis and applied graph theory using Python and NetworkX
    Eric Ma and Mridul Seth

    Are you interested in learning about graph theory and applied network analysis, leveraging your Python skills? Then this is the book for you! See how network science & graph theory connects with a variety of data analysis problems, and use it to solve your next data science challenge!

  6. 研究、生活、幸福
    研究、生活、幸福
    研究生葵花寶典
    Huango

    G>G>G> 研究、生活、幸福。G>G>

  7. 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?

  8. Applied Edge Computer Vision and Machine Learning
    Applied Edge Computer Vision and Machine Learning
    Impatient AI Product Engineering
    Noah Gift

    Focus on building working solutions

  9. 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

  10. Explore Data in Weekend Part I
    Explore Data in Weekend Part I
    Master Exploratory Data Analysis in Weekend
    Hisham El-Amir

    Welcome to the first book in the Week End Series, this series helped me a lot before, and I hope it helps you now. And this book is about the techniques that you should learn to deal with data, any data scientist, and not only data scientists, but every one that faces data problems

  11. Machine Learning Brick by Brick, Epoch 1
    Machine Learning Brick by Brick, Epoch 1
    Using LEGO® to Teach Concepts, Algorithms, and Data Structures
    Dmitry Vostokov

    This machine learning book series aims at providing real hands-on training from general concepts and architecture to low-level details and mathematics. The first epoch covers the simplest linear associative network, proposes a brick notation for algebraic expressions, shows required calculus derivations, and illustrates gradient descent.

  12. Errors of Regression Models
    Errors of Regression Models
    One Stat to Rule Them All
    Lee Baker

    In Errors of Regression Models you’ll learn how to choose the most appropriate statistics to measure the accuracy of your regression-based prediction model.Written in plain English with no technical jargon, Errors of Regression Models is perfect for beginners!Discover how to measure the accuracy of your regression models quickly and effectively.

  13. A Refresher Guide to Convolution Neural Networks
    A Refresher Guide to Convolution Neural Networks
    A Part of Weekend Series
    Hisham El-Amir

    Welcome to one of the On Weekend Series, this series helped me a lot before, and I hope it helps you now. And this book is about the techniques that you should learn to learn, understand and bulid a convolution neural network. I hope you find what you need in this book.

  14. GCP Cloud Architecture
    GCP Cloud Architecture
    Noah Gift, Andrew Nguyen, Alfredo Deza, and Michael Vierling

    Learn to master the Google Cloud platform (GCP).

  15. Get SH*T Done with PyTorch
    Get SH*T Done with PyTorch
    Solve Real-World Machine Learning Problems
    Venelin Valkov

    "Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks." - Stephen Hawking. Learn how to solve real-world problems with Deep Learning models (NLP, Computer Vision, and Time Series). Go from prototyping to deployment with PyTorch and Python!