AI, Machine Learning and Deep Learning

Applications of AI

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Data Science Lifecycle

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Machine Learning Framework

Types of Machine Learning

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Problem understanding

Hands-on: Case study on medical cost prediction

Hands-on: Dataset loading

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Exploratory data analysis

Hands-on: Exploratory data analysis

Hands-on: Data distributions

Hands-on: Data correlations - part 1

Hands-on: Data correlations - part 2

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Data cleaning

Hands-on: Data preprocessing

Hands-on: Removing unused columns

Hands-on: Data encoding and normalization

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Model training & testing

Hands-on: Data splitting

Hands-on: Model training

Hands-on: Model evaluation

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Module Summary

Module cheat sheet

What's next?

Deep Learning applications

Neural Networks

Neural Networks summarization

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XOR example

Update weights

Update weights - part 2

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5 steps to train a Neural Network

Tensorflow & Keras

Keras model lifecycle

Hands-on: Build DL Models

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Data Splitting

Hands-on: Pima Binary Classification

Cross Validation

Hands-on: Cross Validation

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One-Hot Encoding

Hands-on: Classification

Hands-on: Regression

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Keras Callbacks

Hands-on: Advanced concepts

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Module summary

Module cheat sheet

What's next?

What is Computer Vision?

Challenges of Computer Vision

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Image operations

Hands-on: Image Operations

Convolution operation

Hands-on: Image processing

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Keras ImageDataGenerator class

Hands-on: Image Data Preparation - part 1

Hands-on: Image Data Preparation - part 2

Image Augmentation

Hands-on: Image Data Augmentation

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Promise of Deep Learning for Computer Vision

Convolutional Neural Networks (CNN)

Pooling layers

Hands-on: Convolutions & Pooling - Part 1

Hands-on: Convolutions & Pooling - Part 2

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Transfer Learning

Hands-on: Advanced CNN architectures

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Module summary

Module cheat sheet

What's next?

Natural Language

Challenges of Natural Language

NLP applications

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Text cleaning

Hand-on: Data pre-processing

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Feature extraction using Bag-of-words

Hands-on: Bag-of-words

Hands-on: Sentiment Analysis - part 1

Hands-on: Sentiment Analysis - part 2

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The Word Embedding model

Hands-on: Word Embeddings - Part 1

Hands-on: Word Embeddings - Part 2

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Keras' Embedding layer

Sequence problems

Recurrent Neural Network

Hands-on: Deep Sentiment Analysis - Part 1

Hands-on: Deep Sentiment Analysis - Part 2

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Module summary

Module cheat sheet

What's next?

What are Time-series?

Features of Time-series sequences

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Types of Time-series problems

Supervised Learning with Time-series Data

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Understanding Time-series datasets

Hands-on: Case study on power prediction

Hands-on: Dataset loading

Hands-on: Data inspection

Hands-on: Data cleaning - part 1

Hands-on: Data cleaning - part 2

Hands-on: Data preprocessing

Hands-on: Data visualization

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Preparing Time-series datasets

Hands-on: Data preparation - part 1

Hands-on: Data preparation - part 2

Hands-on: Data preparation - part 3

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Building Time-series models

Hands-on: Model training

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Evaluating Time-series models

Hands-on: Model evaluation - part 1

Hands-on: Model evaluation - part 2

Hands-on: Visualizing model performance

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Module summary

Module cheat sheet

A goodbye message from your instructors

Feedback survey

Final words