Convolutional Neural Networks (CNN) Courses and Certifications

Brandon Rohrer

How Convolutional Neural Networks Work, in Depth

Comprehensive exploration of convolutional neural networks, covering their structure, operation, and training process, including key concepts like filtering, pooling, and backpropagation.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Aladdin Persson

EfficientNet Paper Walkthrough

Comprehensive walkthrough of the EfficientNet paper, exploring model scaling, proposed methods, and results. Offers insights into innovative approaches for improving neural network efficiency.

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

DigitalSreeni

Pretrained CNN Features for Semantic Segmentation Using Random Forest

Explore semantic segmentation using VGG16 features and Random Forest, offering improved results for limited training data compared to U-net.

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

DigitalSreeni

Malarial Cell Classification Using CNN

Learn to classify malarial cells using CNN in Python. Covers dataset acquisition, TensorFlow setup, network design, and result analysis for detecting parasitized and healthy cells.

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

Serrano.Academy

A Friendly Introduction to Convolutional Neural Networks and Image Recognition

Friendly explanation of image recognition using Convolutional Neural Networks, covering basics to advanced concepts. Suitable for beginners, with minimal math required.

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

Alexander Amini;  MIT

Convolutional Neural Networks

Explore convolutional neural networks for computer vision, covering feature extraction, convolution operations, and applications in autonomous navigation and medical imaging.

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

Alexander Amini;  MIT

Convolutional Neural Networks

Explore convolutional neural networks for computer vision, covering feature extraction, convolution operations, and applications like object detection and self-driving cars.

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

Alexander Amini;  MIT

Convolutional Neural Networks

Explore convolutional neural networks for computer vision, covering feature extraction, network architecture, and real-world applications like self-driving cars in this comprehensive lecture.

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

Nicholas Renotte

Build a Deep CNN Image Classifier with Any Images

Learn to build a custom deep CNN image classifier from scratch using Python, TensorFlow, and Keras. Covers data pipeline, preprocessing, network building, training, evaluation, and model saving.

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

Code With Aarohi

InceptionV3 - Inception Network

Detailed exploration of InceptionV3 architecture, covering its improvements over previous versions, including factorized convolutions, RMSProp optimizer, and label smoothing for enhanced CNN performance.

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

Code With Aarohi

Explained Identity Block and Convolution Block in ResNet - Residual Networks

Practical explanation of identity and convolutional blocks in ResNet, including line-by-line code breakdown and discussion of residual concepts in deep learning architectures.

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

tinyML

Networks Within Networks - Novel CNN Design Space Exploration for Resource-Limited Devices

Explore novel CNN design for resource-limited devices using "network within network" paradigm. Learn automated method for compressing neural networks while preserving accuracy and meeting size constraints.

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

Augmented Startups

Mask R-CNN - Practical Deep Learning Instance Segmentation Tutorials

Learn to implement and train Mask R-CNN for instance segmentation using OpenCV and Python, covering installation, real-time applications, and custom object detection like potholes.

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

Data Science Dojo

Introduction to Convolutional Neural Networks with TensorFlow

Learn to build and implement convolutional neural networks for image classification using TensorFlow. Gain hands-on experience in deep learning techniques for computer vision tasks.

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

Databricks

Benchmarks and How-Tos for Convolutional Neural Networks on HorovodRunner-Enabled Apache Spark Clusters

Explore benchmarks and implementation techniques for distributed deep learning using HorovodRunner on Apache Spark clusters, focusing on CNN tasks and scaling efficiency for both GPU and CPU clusters.

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