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freeCodeCamp

Deep Learning Crash Course for Beginners

via freeCodeCamp

Overview

This course aims to introduce absolute beginners to the fundamental concepts and terminology of Deep Learning without the need for programming experience. By the end of the course, learners will understand Neural Networks, different Machine Learning constructs, various Neural Network architectures, and the essential steps in building a Deep Learning model. The teaching method involves theoretical explanations and conceptual discussions without any hands-on coding. The course is intended for individuals who are new to Deep Learning and want to grasp its key ideas and applications.

Syllabus

) Introduction.
) What is Deep Learning.
) Introduction to Neural Networks.
) How do Neural Networks LEARN?.
) Core terminologies used in Deep Learning.
) Activation Functions.
) Loss Functions.
) Optimizers.
) Parameters vs Hyperparameters.
) Epochs, Batches & Iterations.
) Conclusion to Terminologies.
) Introduction to Learning.
) Supervised Learning.
) Unsupervised Learning.
) Reinforcement Learning.
) Regularization.
) Introduction to Neural Network Architectures.
) Fully-Connected Feedforward Neural Nets.
) Recurrent Neural Nets.
) Convolutional Neural Nets.
) Introduction to the 5 Steps to EVERY Deep Learning Model.
) 1. Gathering Data.
) 2. Preprocessing the Data.
) 3. Training your Model.
) 4. Evaluating your Model.
) 5. Optimizing your Model's Accuracy.
) Conclusion to the Course.

Taught by

freeCodeCamp.org

Reviews

4.0 rating, based on 1 Class Central review

Start your review of Deep Learning Crash Course for Beginners

  • Profile image for Mehedi Hasan Shojib
    Mehedi Hasan Shojib
    The course is good. I have learned about deep learning in a short time. The basics are well taught. Recommended for crash course enjoyer

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