• What is machine learning?
• Classification Theory
• Regression Theory
• The Neuron
• How does your code “learn” from data?
• Make Predictions
• Saving and Loading a Model
• What will Keras solve?

• Artificial Neural Networks Section Introduction
• Forward Propagation
• Geometric Picture
• Activation Functions
• Multiclass Classifications
• How to represent images?
• Code Preparations (ANN)
• ANN for image classification
• ANN for regression analysis

• What is Convolution?
• Convolution on Colour Images
• CNN Architecture
• CNN Code Presentation
• CNN for MNIST
• Data Augmentation
• Batch Normalization
• Improve the CIFAR-10 Results
• RNN
  • - Sequence data
  • - Forecasting
  • - Autoregressive Linear Model for Time Series Data
  • - Linear model result evaluation
  • - Recurrent Neural Networks
  • - RNN for Time Series Prediction
  • - Paying attention to shapes
  • - GRU ad LSTM
  • - RNN for image classification

• Embedding
• Code Preparation for NLP
• Text Processing
• Text Classification with LSTM
• CNN for text
• Text Classification with CNN

Capstone Project

Any graduate, fresher, experienced and looking to start or change their career into data analytics can attend. No prior experience is mandatory.

Absolutely. We start the training from scratch. After completing the course you will not feel that you have never programmed.

Yes

Our trainers are from the industry. Every class is followed by real time assignments which will make you feel confident when you get into a job.

Fully online. You can attend from anywhere. You just need a laptop and a good internet connection

Yes 100%. It is live and fully interactive. We don't believe in running through power point presentations.

Please contact on the given number.