Perceptron Courses and Certifications

Deep Learning: Getting Started

1254 ratings at LinkedIn Learning

Learn the basics of deep learning and get up and running with this technology.

• LinkedIn Learning
• 1 hour 14 minutes
• On-Demand
• Free Trial Available

Artificial Intelligence Foundations: Neural Networks

647 ratings at LinkedIn Learning

Learn the fundamental techniques and principles behind artificial neural networks.

• LinkedIn Learning
• 1 hour 45 minutes
• On-Demand
• Free Trial Available

Learn the basics of Machine Learning in this introductory course.

• Codecademy
• 20 hours
• On-Demand
• Free Trial Available

Great Learning

Artificial Intelligence Tutorial for Beginners - AI Full Course

Keeping the importance of artificial intelligence in mind, we have come up with this full course on Artificial Intelligence.

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

Alexander Amini;  MIT

MIT: Introduction to Deep Learning

Foundations of deep learning: perceptrons, neural networks, loss functions, backpropagation, optimization techniques, and strategies to prevent overfitting in neural network training.

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

Alexander Amini;  MIT

Introduction to Deep Learning - MIT 2018

Explore foundations of deep learning, including perceptrons, neural networks, loss functions, and optimization techniques. Gain insights into training challenges and strategies for effective model development.

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

Alexander Amini;  MIT

MIT Introduction to Deep Learning

Comprehensive introduction to deep learning fundamentals, covering perceptrons, neural networks, loss functions, gradient descent, backpropagation, and regularization techniques for building effective models.

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

Alexander Amini;  MIT

Introduction to Deep Learning

Comprehensive introduction to deep learning fundamentals, covering perceptrons, neural networks, loss functions, gradient descent, backpropagation, and regularization techniques for building effective models.

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

Alexander Amini;  MIT

Introduction to Deep Learning

Comprehensive introduction to deep learning fundamentals, covering perceptrons, neural networks, loss functions, gradient descent, backpropagation, and regularization techniques.

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

Krish Naik

Deep Learning Indepth Tutorials With Krish Naik

Comprehensive deep learning tutorial covering key concepts, techniques, and practical implementations, from perceptrons to CNNs, with hands-on examples and expert insights.

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

Python Engineer

Machine Learning From Scratch in Python - Full Course With 12 Algorithms

Comprehensive Python implementation of 12 popular machine learning algorithms from scratch, covering KNN, regression, SVM, decision trees, random forests, PCA, K-means, AdaBoost, and LDA.

• YouTube
• 4 hours 55 minutes
• On-Demand
• Free Video

Alexander Amini

MIT Introduction to Deep Learning

Comprehensive introduction to deep learning fundamentals, covering perceptrons, neural networks, loss functions, gradient descent, backpropagation, and regularization techniques.

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

Alexander Amini

MIT Introduction to Deep Learning

Comprehensive introduction to deep learning fundamentals, covering perceptrons, neural networks, loss functions, gradient descent, backpropagation, and regularization techniques.

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

NDC Conferences

A Friendly Introduction to Deep Learning for Computer Vision

Explore deep learning for computer vision, from basic concepts to advanced neural networks, with easy-to-understand examples and PyTorch demonstrations.

• YouTube
• 59 minutes
• On-Demand
• Conference Talk

Redes Neurais Artificiais em Python

3310 ratings at Udemy

Aprenda na teoria e na prática os fundamentos das redes neurais em Python e entre para o mundo do Deep Learning!

• Udemy
• 8 hours 15 minutes
• On-Demand
• Paid Course