Gradient Descent Courses and Certifications

Centre de recherches mathématiques - CRM

Scaling Laws for Gradient Descent and Sign Descent for Linear Bigram Models under Zipf's Law

Explore optimization challenges in transformer language models through linear bigram analysis, examining how Zipf's law affects gradient descent performance and sign descent improvements.

• YouTube
• 1 hour 25 minutes
• On-Demand
• Free Video

NPTEL-NOC IITM

Gradient Descent Using Python

Master gradient descent implementation in Python through hands-on coding techniques and mathematical optimization principles in this concise tutorial.

• YouTube
• 12 minutes
• On-Demand
• Free Video

NPTEL-NOC IITM

Statistical Modeling: Gradient Descent

Dive into gradient descent, a key optimization algorithm for statistical modeling, and understand its principles and applications.

• YouTube
• 18 minutes
• On-Demand
• Free Video

AutoML Seminars

Gradient Descent: The Ultimate Optimizer - Automating Hyperparameter Optimization

Discover how to automatically optimize hyperparameters in gradient-based ML algorithms through an elegant modification to backpropagation, making optimizer tuning more efficient and less sensitive to initial choices.

• YouTube
• 30 minutes
• On-Demand
• Free Video

Simons Institute

Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression

Explore the statistical benefits of early stopping in gradient descent for overparameterized logistic regression, including its regularization effects and advantages over asymptotic approaches.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Regression and Gradient Descent

Master regression algorithms and gradient descent by building them from scratch, covering linear and logistic regression without relying on high-level libraries.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Packt

Matrix Calculus for Data Science & Machine Learning

Master the fundamentals of matrix calculus for data science applications, including vector derivatives, optimization techniques, and practical implementations in Python for machine learning algorithms.

• Coursera
• 8 hours 55 minutes
• On-Demand
• Paid Course

Gradient Boost

Explore the fundamentals and advanced concepts of Gradient Boost for regression and classification in machine learning.

• YouTube
• 1 hour 30 minutes
• On-Demand
• Free Video

Simons Institute

Optimization Crash Course

Explore geometric methods in optimization and sampling, covering key topics like convexity, optimality, and gradient descent with expert insights from MIT's Ashia Wilson.

• YouTube
• 42 minutes
• On-Demand
• Free Video

MITCBMM

Optimization

Explore optimization techniques for machine learning, covering likelihood estimation, cost functions, gradient descent, and regularization methods for improved model performance.

• YouTube
• 56 minutes
• On-Demand
• Free Video

Valerio Velardo - The Sound of AI

Training a Neural Network - Implementing Backpropagation and Gradient Descent from Scratch

Implement backpropagation and gradient descent from scratch in Python, training a neural network to perform arithmetic sum. Includes step-by-step coding and explanations.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Valerio Velardo - The Sound of AI

Training a Neural Network - Backward Propagation and Gradient Descent

Explore the theory and mathematics behind neural network training, focusing on backpropagation and gradient descent algorithms for deep learning enthusiasts.

• YouTube
• 22 minutes
• On-Demand
• Free Video

Introduction to Deep Learning

1 rating at Udacity

Explore foundational deep learning theory and practice, covering key algorithms, architectures, and implementation in PyTorch. Develop skills to design and train neural networks for real-world applications.

• Udacity
• 20 hours
• On-Demand
• Paid Course

Introduction to Neural Networks with TensorFlow

Learn the fundamentals of neural networks with Python and TensorFlow, and then use your new skills to create your own image classifier—an application that will first train a deep learning model on a dataset of images and then use the trained model to cla…

• Udacity
• 17 hours
• On-Demand
• Paid Course

Introduction to Neural Networks with PyTorch

Learn the fundamentals of neural networks with Python and PyTorch, and then use your new skills to create your own image classifier—an application that will first train a deep learning model on a dataset of images and then use the trained model to classi…

• Udacity
• 17 hours
• On-Demand
• Paid Course