Yacine Mahdid Courses

Learning Machine Learning Efficiently

1 rating

Discover an efficient approach to learning machine learning, exploring the landscape, optimal paths, and practical strategies for mastering this complex field.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Intersection over Union (IoU) Explained with PyTorch

Learn to implement Intersection over Union (IoU) for object recognition using PyTorch. Covers theory, formulas, and practical code for bounding boxes and segmentation masks.

• YouTube
• 18 minutes
• Self-Paced
• Free Video

GoogLeNet Deep Neural Network Explained - Inception V1 Architecture and Implementation

Explore GoogLeNet's 22-layer deep neural network architecture, its Inception modules, and Pytorch implementation. Learn about its design principles and performance on image classification tasks.

• YouTube
• 23 minutes
• Self-Paced
• Free Video

FractalNet Deep Neural Network Explained

Explore FractalNet, an alternative to residual networks, through paper analysis and PyTorch implementation. Learn about fractal expansion, drop path, and performance comparisons with ResNet.

• YouTube
• 36 minutes
• Self-Paced
• Free Video

Stochastic Depth for Neural Networks - Implementation and Analysis

Explore stochastic depth in neural networks: a regularization method for residual networks that enhances training speed and test performance. Includes methodology explanation and PyTorch implementation.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Structuring Data Science Projects with Docker

Structure data science projects using Docker for seamless model deployment. Learn advanced techniques, explore code, address vulnerabilities, and weigh pros and cons of Docker in data science workflows.

• YouTube
• 13 minutes
• Self-Paced
• Free Video

Log Softmax Explained with Python

Explore log softmax implementation in Python, enhancing numerical stability for machine learning. Gain insights into softmax limitations and practical coding solutions.

• YouTube
• 12 minutes
• Self-Paced
• Free Video

DenseNet Deep Neural Network Architecture Explained

Comprehensive explanation of DenseNet architecture, including its benefits and implementation in PyTorch. Covers theory, results, and practical coding walkthrough for deep learning enthusiasts.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

Img2Vec and UMAP for High-Dimensional Data Visualization

Learn to visualize high-dimensional image data using Img2Vec for embeddings, UMAP for dimensionality reduction, and Bokeh for interactive exploration. Ideal for vision classification projects.

• YouTube
• 50 minutes
• Self-Paced
• Free Video

QHAdam Optimizer - Theory and Implementation in PyTorch

Dive into the theory and implementation of QHAdam optimizer, exploring its formulas, performance benefits, and practical PyTorch implementation through detailed code examples and mathematical breakdowns.

• YouTube
• 54 minutes
• Self-Paced
• Free Video

How to Read Math in Deep Learning Papers - A 5-Step Process

Learn a 5-step method to decipher mathematical formulas in deep learning papers, enhancing your understanding and intuition of complex AI concepts.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Practical Guide to Implementing AI Projects in Business

Master practical steps for implementing AI projects in business settings, from problem identification and data structuring to solution iteration and deployment.

• YouTube
• 10 minutes
• Self-Paced
• Free Video

MiniMax-01 Theory Overview - Lightning Attention + MoE + FlashAttention Optimization

Explore MiniMax-01's architecture featuring Lightning Attention, MoE, and FlashAttention optimizations that enable a 4M token context window and 456B parameters, outperforming Llama 3.1 and challenging Claude in benchmarks.

• YouTube
• 47 minutes
• Self-Paced
• Free Video

A Systematic Approach to Reading Deep Learning Codebases

Master a systematic approach to understanding complex deep learning codebases, from initial paper review to mapping structure and components, with practical examples using SAM1.

• YouTube
• 15 minutes
• Self-Paced
• Free Video

Guide to Scientific Research in Undergraduate Studies - From Lab Selection to Success

Discover a proven step-by-step approach to securing undergraduate research positions in labs, from identifying your interests and time commitment to successfully landing and maximizing research opportunities.

• YouTube
• 14 minutes
• Self-Paced
• Free Video