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Artificial Intelligence (AI ) and Deep Learning Advance Training

  • Course Content
  • Drop us a Query

AI Basics (Theory)

  • Introduction and scope
  • Understanding Intelligent agents
  • Problem Solving e.g Adversarial Search
  • Knowledge representation
  • Probabilistic reasoning

Machine Learning foundation

  • Supervised Learning
  • Unsupervised Learning - SVM
  • Decision trees - Clustering
  • Artificial Neural network
  • Practical ML (hands on)

Deep Learning foundation

  • Introduction, motivation for deep learning
  • Set up Anaconda, Jupyter Notebooks
  • Applying Deep learning
  • Regression

Neural networks

  • Maths refresher, Introduction to NumPy, Tensorflow - introduction
  • Introduction to Neural Network : Covers in details Perceptron, Gradient descent, multilayered perceptron, Back propagation
  • Build your first neural network
  • Model evaluation and validation
  • Project : Sentiment Analysis of movie reviews
  • Develop a mini version of neural network library like Tensorflow

Convolutional Neural Networks

  • Intro to Tensorflow
  • Using Cloud computing hardware for computations
  • Deep Neural networks
  • CNN - theory, how and why does it works ?
  • Project : Build an Image classifier
  • Image generation

Recurrent Neural Networks

  • Introduction to RNN
  • Long Short Term memory
  • LSTM Cell - detailed walkthrough and implementation
  • Build a RNN
  • Mini Project : Stock price prediction (self proctored)
  • Embeddings and Word2Vec
  • Sentiment prediction RNN
  • Text summarization - using Keras
  • Project : Generate TV Scripts
  • Designing a Chatbot
  • Buid a language translator

Generative Adversarial Networks (advanced)

  • Introduction to GAN
  • How GANs work
  • Games and Equilibria
  • Build and train a GAN
  • Project: Generate faces : Build 2 NNs to compete with each other to generate realisitic human faces

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