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Looking for an AI buddy(s): Learning and Impelementing

18th June, 2024
Last date to join: 2nd July, 2024

Hey everyone! I'm looking for a buddy or a group of buddies who are interested in learning foundations of data science and machine learning with me. I'm already a bit experienced in the area myself so I can help you get started (if you are a complete beginner). I will be consulting Hands-On Machine Learning throughout my learning journey for conceptual clarity and practice. Moreover, we can also implement some basic projects once done with some major algorithms and concepts. I further plan on learning MLOps too so let me know if you might be interested in that. If more people happen to respond, I can create a discord server too.

Novice English

Description

Through a series of recent 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 practical book shows you how.

By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.

  • Explore the machine learning landscape, particularly neural nets
  • Use Scikit-Learn to track an example machine-learning project end-to-end
  • Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods
  • Use the TensorFlow library to build and train neural nets
  • Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning
  • Learn techniques for training and scaling deep neural nets

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition

Start Learning
Books
O'Reilly Media
Exclusively Paid
24h 18m
No Certificate
848 pages

Looking for an AI buddy(s): Learning and Impelementing

18th June, 2024
Last date to join: 2nd July, 2024
Start Learning
Affiliate notice

Hey everyone! I'm looking for a buddy or a group of buddies who are interested in learning foundations of data science and machine learning with me. I'm already a bit experienced in the area myself so I can help you get started (if you are a complete beginner). I will be consulting Hands-On Machine Learning throughout my learning journey for conceptual clarity and practice. Moreover, we can also implement some basic projects once done with some major algorithms and concepts. I further plan on learning MLOps too so let me know if you might be interested in that. If more people happen to respond, I can create a discord server too.

Novice English

  • Type
    Books
  • Provider
    O'Reilly Media
  • Pricing
    Exclusively Paid
  • Duration
    24h 18m
  • Certificate
    No Certificate
  • Pages
    848 pages

Through a series of recent 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 practical book shows you how.

By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.

  • Explore the machine learning landscape, particularly neural nets
  • Use Scikit-Learn to track an example machine-learning project end-to-end
  • Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods
  • Use the TensorFlow library to build and train neural nets
  • Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning
  • Learn techniques for training and scaling deep neural nets

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Join a group of like-minded people who want to learn and grow alongside you

Frequently asked questions

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

2nd July, 2024

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