Hyperparameters Courses and Certifications

Introduction to Deep Learning with PyTorch

43 ratings at DataCamp

Learn how to build your first neural network, adjust hyperparameters, and tackle classification and regression problems in PyTorch.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Advanced Computer Vision and Deep Learning

1 review

Learn to apply deep learning architectures to computer vision tasks. Discover how to combine CNN and RNN networks to build an automatic image captioning application.

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

Building Reusable Pipeline Functions

Discover how to build modular MLOps pipeline components for data processing, model training, evaluation, and persistence that form the foundation for automated ML workflows.

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

Data Science: Supervised Machine Learning in Python

3554 ratings at Udemy

Full Guide to Implementing Classic Machine Learning Algorithms in Python and with Scikit-Learn

• Udemy
• 6 hours 25 minutes
• On-Demand
• Paid Course

Machine Learning - Regression and Classification (math Inc.)

486 ratings at Udemy

A complete Beginner to Advance level guide to Machine Learning. Hands-on Learning approach with in-depth math concepts

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

Classification and Planned Experiments

Master classification techniques like K-nearest neighbor and logistic regression, plus experimental design principles for causal analysis using R and Python.

• Coursera
• 4 hours 47 minutes
• On-Demand
• Paid Course

Generative AI Skillpath: Zero to Hero in Generative AI

84 ratings at Udemy

Complete course on Generative AI: Prompting Engineering, Running LLMs locally (Ollama), Building AI apps using LangChain

• Udemy
• 11 hours 43 minutes
• On-Demand
• Paid Course

Coursera

TensorFlow for Beginners: Basic Binary Image Classification

Learn to build and train a neural network for classifying cat and dog images using TensorFlow. Covers data preprocessing, CNN architecture, hyperparameter tuning, and model evaluation techniques.

• Coursera
• 3 hours 12 minutes
• On-Demand
• Paid Course

Coursera

Build & Evaluate Decision Trees for ML

Master decision tree algorithms in Java using Weka and Smile libraries. Build, tune, and evaluate models with entropy, Gini index, and cross-validation techniques for real-world ML applications.

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

Julia Silge

Tuning Random Forest Hyperparameters with Tidymodels

Learn to optimize random forest models using tidymodels, exploring hyperparameter tuning techniques with San Francisco tree data for improved predictive performance.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Video

Neural Networks and Convolutional Neural Networks Essential Training

530 ratings at LinkedIn Learning

Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning.

• LinkedIn Learning
• 1 hour 19 minutes
• On-Demand
• Free Trial Available

Unlock the power of conversational AI by mastering system prompts, message history, Few Shot Learning, and hyperparameters like Temperature and Top P in the OpenAI API Playground.

• Codecademy
• On-Demand
• Free Trial Available

Toronto Machine Learning Series (TMLS)

AutoML Towards Deep Learning: Optimizing Neural Architectures and Hyperparameters

Explore advances in AutoML for Deep Learning, focusing on joint optimization, efficiency, and robustness. Learn about the future of automated neural architecture and hyperparameter optimization.

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

Center for Language & Speech Processing(CLSP), JHU

Learning Neural Network Hyperparameters for Machine Translation - 2019

Explore neural network hyperparameter optimization for machine translation, focusing on efficient methods to learn parameters during training without extensive grid searches.

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

EDGE AI FOUNDATION

Sensitivity Analysis of Hyperparameters in Deep Neural-Network Pruning

Explore the impact of hyperparameter sensitivity in neural network pruning for optimizing model performance on resource-constrained devices through empirical analysis and optimization techniques.

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