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Study Group for hands-on machine learning with scikit-learn, keras, and tensorflow

4th June, 2021
Last date to join: 30th June, 2021

Hi, I recently started the book "hands-on machine learning with scikit-learn, keras, and tensorflow" by Aurelien Geron. Problem is I am not accountable to anyone, so there is a lot of dilettantism about my approach. If anyone is interested in creating a study group of sorts and complete the entire book, do let me know. Idea would be to cover a chapter every two weeks with a kaagle challenge on the same completed by end of the two weeks.

Novice English

Description

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.

With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started.

  • Use Scikit-learn to track an example ML project end to end
  • Explore several models, including support vector machines, decision trees, random forests, and ensemble methods
  • Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection
  • Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers
  • Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 3rd Edition

Start Learning
Books
O'Reilly Media
Exclusively Paid
25h 32m
No Certificate
861 pages

Study Group for hands-on machine learning with scikit-learn, keras, and tensorflow

4th June, 2021
Last date to join: 30th June, 2021
Start Learning
Affiliate notice

Hi, I recently started the book "hands-on machine learning with scikit-learn, keras, and tensorflow" by Aurelien Geron. Problem is I am not accountable to anyone, so there is a lot of dilettantism about my approach. If anyone is interested in creating a study group of sorts and complete the entire book, do let me know. Idea would be to cover a chapter every two weeks with a kaagle challenge on the same completed by end of the two weeks.

Novice English

  • Type
    Books
  • Provider
    O'Reilly Media
  • Pricing
    Exclusively Paid
  • Duration
    25h 32m
  • Certificate
    No Certificate
  • Pages
    861 pages

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.

With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started.

  • Use Scikit-learn to track an example ML project end to end
  • Explore several models, including support vector machines, decision trees, random forests, and ensemble methods
  • Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection
  • Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers
  • Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning

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Yes. Our study groups (all of them) are free to join

You join the group and study the MOOC together on a schedule. The exact dates, deadlines, are created by the host

This depends on the host of your group. Some groups have weekly video calls for accountability + doubt solving.

Moocable is a community where you can find study partners, mentors, or people to collaborate on projects. It's designed for people who want to upskill, but struggle with self-learning. Users often post about their skills, goals, and what they're looking to learn or work on, and others can respond to form partnerships or groups. You can join our community

30th June, 2021

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