Deep Learning with Dr. Shazia Saqib

Description

What Will You Learn in this Course?

·  Artificial Intelligence and its Applications

·  Machine Learning Fundamentals

·  Supervised Learning 

·  Unsupervised Learning

·  Reinforcement Learning

·  Regression

·  Classification 

·  Hidden Markov Model.

·  Support Vector Machines.

·  Limitations of Machine Learning.

·  Perception.

·  Tensorflow.

·  Computational Graph.

·  Backpropagation.

·  Artificial Neural Network and Applications.

·  Confusion Matrix.

·  Cost Function.

·  Bias Variance.

·  Building Neural Networks.

·  Layers of Neural Networks.

·  How CNN Works

·  Inception Networks

·  Recurrent Neural Networks

·  Natural Language Processing 

·  Sentiment Classification

·  YOLO

·  Autoencoders

·  Neural Style Networks and Its Applications

·  Project (Sentiment Analysis for Motivational Videos/Neural Style Transfer based Textile Designing)

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