• Intro to AI & Neural Networks
• Deep Learning vs Machine Learning
• Tech Advancement
• All about Artificial Neural Networks (ANN)
• Understand How Deep Neural Network Works?
• Different variants of Gradient Descent
• Stochastic Gradient Descent vs Adam vs Others
• Hyper parameter Tuning
• Batch Size
• Learning Rate
• Momentum
   
• Deep Learning in Python
• Deep Learning packages in python
• Google TensorFlow Framework
• Model Building with default TFLearn API
• Keras Vs TFLearn Vs Pycharm APIs
• Model Building with Keras API Wrapper
• Activations
• Optimizers
• Losses
• Validation
• Evaluation Metrics
• Keras Backend
• Callbacks - Early Stopping, TensorBoard
   
• CNN - Convolutional Neural Networks
• Understanding Architecture & Visualizing a CNN
• Stochastic Gradient Descent vs Adam vs Others
• Hyper parameter Tuning
• Batch Size
• Learning Rate
• Momentum
   
• Transfer Learning
• vgg16
  • Activations
  • Optimizers
  • Losses
  • Validation
  • Evaluation Metrics
  • Keras Backend
  • Callbacks - Early Stopping, TensorBoard
• vgg19
  • Kernel
  • Depth
  • Pooling
• resnrt 50
   
• NLTK
• Simple NLTK
  • Stemming
  • Lemitaization
  • Regex
  • Stopwords
  • Corpus
  • Unigram
  • Bigram
  • Trigram
• BAG fo words(count vectorization)
• TD-IDF-term frequency inverse document frequency 1
• Word embedding
  • word 2 vec --cbow / skipgram
  • glove
• Fasttext
• Keyed vector
• LSTM / RNN (bidirentional)
• GRU(theory - Arthiecture build )
   
• Projects & Case Studies
• Image Recognition using MNIST Dataset
• Object Recognition using CIFAR-10 Dataset
• Speech Recognition (Google Voice | Alexa | Siri)
• Sentiment Analysis and Word Clouds
• Chat Bot Building
• Please Note - Case studies / projects changes from time to time and will be covered along with their respective modules.