Tomadora
Deep Learning from Scratch
AI-generated course for Machine Learning & AI covering: Module 1: Foundations of Deep Learning and Essential Mathematics, Module 2: The Perceptron and Feedforward Neural Networks, Module 3: Backpropagation and Gradient Descent, Module 4: Advanced Optimization Algorithms, Module 5: Regularization and Model Generalization, Module 6: Convolutional Neural Networks (CNNs) for Computer Vision, Module 7: Sequence Modeling with RNNs and LSTMs, Module 8: Unsupervised Deep Learning Architectures
Beginner
11 lessons
214 questions
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What you'll learn
This course is part of the Machine Learning & AI track on Tomadora. It covers 3 progressive modules with 11 bite-sized lessons, totalling 214 interactive questions including flashcards, multiple choice, true/false, typing, matching, and fill-in-the-blank.
Course syllabus
Module 1: Foundations of Deep Learning and Essential Mathematics
An introduction to the fundamental concepts of deep learning, including the essential linear algebra, probability, and calculus required to understand neural network operations.
- Introduction to Neural Networks and Deep Learning (28 questions)
- Linear Algebra Essentials (7 questions)
- Calculus for Optimization (27 questions)
- Probability and Cost Functions (27 questions)
Module 2: The Perceptron and Feedforward Neural Networks
Learn how to build the building blocks of deep learning by constructing a simple perceptron, understanding activation functions, and designing multi-layer feedforward neural networks.
- The Perceptron Model (4 questions)
- Multilayer Perceptrons (MLPs) (26 questions)
- Activation Functions (27 questions)
- Forward Propagation (27 questions)
Module 3: Backpropagation and Gradient Descent
Dive into the mechanics of learning by exploring loss functions, the chain rule, gradient descent, and how backpropagation updates network weights to minimize errors.
- Introduction to Gradient Descent (28 questions)
- The Chain Rule and Computational Graphs (13 questions)
- Implementing Backpropagation from Scratch
Frequently asked questions
- What is the Deep Learning from Scratch course?
- Deep Learning from Scratch is a beginner course on Tomadora covering 3 modules and 11 lessons. It is designed to be completed in 5-minute bursts during your work breaks, using a Pomodoro-style focus + learn cycle.
- How long does Deep Learning from Scratch take to finish?
- Each lesson takes about 5 minutes. With 11 lessons, you can finish the course in roughly 1 hours of total learning time, spread across as many breaks as you like.
- Is Deep Learning from Scratch free?
- Yes. Tomadora is free to download and the entire Machine Learning & AI track — including Deep Learning from Scratch — is free to learn.
- What level is Deep Learning from Scratch?
- Deep Learning from Scratch is rated Beginner. No prior knowledge is required.
- What language is Deep Learning from Scratch taught in?
- Deep Learning from Scratch is taught in English.
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