/deep-learning-specialization

Deep Learning Specialization

(Standford online / DeepLearning.AI curriculum offered via Coursera)

DL Specialization url

This repository provides an overview of the courses taken and the skills I gained through completion of the specialization. (In accordance with Coursera's honor code, course work/code cannot be shared.)

Specialization Skills

  • Tensorflow
  • Artificial Neural Networks
  • Convolutional Neural Networks
  • Recurrent Neural Networks
  • Transformers
  • Python Programming
  • Deep Learning
  • Backpropagation
  • Optimization
  • Hyperparameter Tuning
  • Machine Learning
  • Transfer Learning
  • Multi-Task Learning
  • Object Detection and Segmentation
  • Facial Recognition System
  • Gated Recurrent Unit (GRU)
  • Long Short Term Memory (LSTM)
  • Attention Models
  • Natural Language Processing

Courses and Modules

Neural Networks and Deep Learning

  • Introduction to Deep Learning
  • Neural Networks Basics
  • Shallow Neural Networks
  • Deep Neural Networks

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization, and Optimization

  • Practical Aspects of Deep Learning
  • Optimization Algorithms
  • Hyperparameter tuning, Batch Normalization, and Programming Frameworks

Structuring Machine Learning Projects

  • ML Strategy 1
  • ML Strategy 2

Convolutional Neural Networks (CNN)

  • Foundations of Convolutional Neural Networks
  • Deep Convolutional Models: Case Studies
  • Object Detection
  • Special Applications: Face Recognition and Neural Style Transfer

Sequence Models

Recurrent Neural Networks

  • Natural Language Processing and Word Embeddings
  • Sequence Models and the Attention Mechanism
  • Transformers