puzzle branch paper paper message user-group

Warning: Invalid argument supplied for foreach() in /users/radixlibrary/www/views/layout/header1.php on line 404
Login
×
  • Radix
  • Learning Paths
  • Resources
  • Login
  • ×
























    Reviews
    Curator
    Path tree
    Overview

    Reviews

    Curator

    Path tree

    Machine Learning 3

    Machine Learning is a broad research field with many successful applications in real life. Python is hereby the most common tool to build ML models.

    Curated by Camillo

    Beginner Lvl 1
    8h
    5.3k
    4.6(21,556)

    Python Apply machine learning with

    1%
    Filter Paths
    Continue
    Top 3
    1. Module
    40

    Scikit-Learn

    This library is built on NumPy, SciPy, and matplotlib and contains algorithms on classification, regression, clustering, dimensionality reduction, model selection, preprocessing

    With this library, you will be able to build your first Machine Learning models.Start by looking at the examples!

    MARK AS DONE
    Author:    
    Time required: 8h
    Cost: 0€
    40

    Machine Learning with Python

    This course will introduce you to the basics of the Machine. The course will use ___tool. We will use the Scikit-Learn, TensorFlow library to get a high-level intuition and understanding of algorithms, regression, classification, neural networks

    These videos guide you through applying several ML algorithms from Scikit-Learn!

    MARK AS DONE
    Author: sentdex    
    Time required: 8h
    Cost: 0€
    40

    Machine Learning Recipes with Josh Gordon

    Google Inc.

    Explanations and guidance on basic ML programming, SciKit, Weka, TensorFlow

    MARK AS DONE
    Author: Josh Gordon   
    Time required: 8h
    Cost: 0€
    2. Module
    40

    TensorFlow

    Google

    This library entails various deep learning algorithms.

    To start, run the code of the numerous tutorials!

    MARK AS DONE
    Author:    
    Time required: 8h
    Cost: 0€
    40

    Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow

    O'Reilly Media, Inc.

    You should read this book if you want to better understand the algorithms and applications of Scikit-Learn, Keras, and TensorFlow libraries.

    This book entails everything you need to know about machine learning and deep learning!

    MARK AS DONE
    Author: Aurélien Géron   
    Time required: 8h
    Cost: 0€
    40

    Chris Albon

    Code snippets on data manipulation, preprocessing, machine Learning, deep learning, statistics

    Go through the very helpful code blocks!

    MARK AS DONE
    Author:    
    Time required: 8h
    Cost: 0€
    3. Module
    40

    Python Data Science Handbook

    O'Reilly Media

    This book will emcompasses data manipulation with Pandas, visualization with Matplotlib, Machine Learning with Scikit-Learn

    This book provides a good overview and serves as a additional resource!

    MARK AS DONE
    Author: Jake VanderPlas   
    Time required: 8h
    Cost: 0€
    40

    AI Hub

    Google Inc.

    This platform has one purpose, and that is to share collection of interactive machine learning examples on classification, unsupervised, recurrent nets, generative, basic ml, images & video, sounds & music, text & language.

    Look through and try to run these interesting Machine Learning examples!

    MARK AS DONE
    Author:    
    Time required: 8h
    Cost: 0€
    4. Module
    40

    Kaggle

    Community of data scientists, machine learning competitions, datasets

    As a starting point, check the "Titanic: Machine Learning from Disaster" challenge! Otherwise, pick one of your interest and participate!

    MARK AS DONE
    Author:    
    Time required: 8h
    Cost: 0€
    40

    PyTorch

    Facebook

    Open source deep learning platform that provides a seamless path from research prototyping to production deployment

    This framework enjoys a huge popularity, especially among researchers!

    MARK AS DONE
    Author:    
    Time required: 8h
    Cost: 0€
    5. Extras