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Generate Income with Artificial Intelligence

Everything you need to know to generate income with AI nowadays

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Course Overview

  • Beginner to Pro
  • 192 lectures
  • 23 hours of HD video
  • Downloadable content
  • Hands-on exercises
  • English captions
  • Certificate of completion
  • Lifetime access
  • Learn at your own pace

Clear. Concise. Comprehensive.

Tired of piecing together disconnected tutorials or dealing with rambling, confusing instructors? This course is for you! It's perfectly structured into a series of bite-sized, easy-to-follow videos that cover both theory and practice.

Highly practical

What You'll Learn

  • Understand the intuition behind Artificial Neural Networks
  • Develop real-world apps to build your portfolio and impress potential employers
  • Apply Artificial Neural Networks in practice
  • Open up new career opportunities and increase your earning potential
  • Stay up-to-date with latest technologies and trends
A perfectly structured course

Course Content

23 Hours . 27 Sections . 192 Lessons

Getting Started(33m)

  • What is Deep Learning?Preview
  • Get the Datasets herePreview
  • Use ChatGPT to Boost your Deep Learning SkillsPreview

Artificial Neural Networks(1h 18min)

  • Business Problem Description4m 59s
  • Building an ANN - Step 110m 21s
  • Building an ANN - Step 218m 36s
  • Building an ANN - Step 314m 28s
  • Building an ANN - Step 411m 58s
  • Building an ANN - Step 516m 25s

Convolutional Neural Networks(1h 41m)

  • What You'll Need for CNN2m 04s
  • Plan of attack3m 31s
  • What are convolutional neural networks?15m 49s
  • Step 1 - Convolution Operation16m 38s
  • Step 1(b) - ReLU Layer6m 41s
  • Step 2 - Pooling14m 13s
  • Step 3 - Flattening1m 52s
  • Step 4 - Full Connection19m 24s
  • Summary4m 19s
  • Softmax & Cross-Entropy18m 20s

Recurrent Neural Networks(1h 12m)

  • What You'll Need for RNN2m 24s
  • Plan of attack2m 32s
  • The idea behind Recurrent Neural Networks16m 01s
  • The Vanishing Gradient Problem14m 27s
  • LSTMs19m 48s
  • Practical intuition15m 11s
  • EXTRA: LSTM Variations3m 36s

Self Organism Maps Intuition(1h 31m)

  • Plan of attack3m 10s
  • How do Self-Organizing Maps Work?8m 30s
  • Why revisit K-Means?2m 19s
  • K-Means Clustering (Refresher)14m 17s
  • How do Self-Organizing Maps Learn? (Part 1)14m 24s
  • How do Self-Organizing Maps Learn? (Part 2)9m 37s
  • Live SOM example4m 28s
  • Reading an Advanced SOM14m 26s
  • EXTRA: K-means Clustering (part 2)7m 48s
  • EXTRA: K-means Clustering (part 3)11m 51s
  • How to get the dataset1m 32s
  • Building a SOM - Step 113m 49s
  • Building a SOM - Step 29m 39s
  • Building a SOM - Step 317m 25s
  • Building a SOM - Step 411m 12s
  • Mega Case Study31m

Boltzmann Machines(4h)

  • Plan of attack2m 24s
  • Boltzmann Machine14m 22s
  • Energy-Based Models (EBM)10m 39s
  • Editing Wikipedia - Our Contribution to the World3m 28s
  • Restricted Boltzmann Machine17m 29s
  • Contrastive Divergence16m 28s
  • Deep Belief Networks5m 23s
  • Deep Boltzmann Machines2m 57s
  • How to get the dataset1m 32s
  • Installing PyTorch3m 28s
  • Building a Boltzmann Machine - Introduction9m 9s
  • Same Data Preprocessing in Parts 5 and 62m 58s
  • Building a Boltzmann Machine - Step 1-142h 41m
  • Evaluating the Boltzmann Machine2m 39s

AutoEncoders Intuition(39m)

  • Plan of attack2m 12s
  • Auto Encoders10m 50s
  • A Note on Biases1m 15s
  • Training an Auto Encoder6m 10s
  • Overcomplete hidden layers3m 52s
  • Sparse Autoencoders3m 13s
  • Denoising Autoencoders2m 32s
  • Contractive Autoencoders2m 23s
  • Stacked Autoencoders1m 54s
  • Deep Autoencoders1m 50s

Building an Autoencoder(2h 19m)

  • How to get the dataset1m 32s
  • Installing PyTorch1m 19s
  • Same Data Preprocessing in Parts 5 and 61m 35s
  • Building an AutoEncoder - Step 1-342m 27s
  • Homework Challenge - Coding Exercise1m 01s
  • Building an AutoEncoder - Step 4-111h 26m

Annex - Get the Machine Learning Basics(28m)

  • Annex - Get the Machine Learning Basics1m 49s
  • What You Need for Regression & Classification1m 23s
  • Simple Linear Regression Intuition - Step 16m 04s
  • Simple Linear Regression Intuition - Step 23m 40s
  • Multiple Linear Regression Intuition1m 49s
  • Logistic Regression Intuition17m 48s

Data Preprocessing(1h 52m)

  • Data Preprocessing1m 41s
  • The Machine Learning process2m 36s
  • Splitting the data into a Training and Test set2m 51s
  • Feature Scaling6m 54s
  • Getting Started - Step 15m 25s
  • Getting Started - Step 25m 21s
  • Importing the Libraries3m 36s
  • Importing the Dataset - Step 15m 28s
  • Importing the Dataset - Step 24m 48s
  • Importing the Dataset - Step 35m 46s
  • For Python learners, summary of Object-oriented programming1m 39s
  • Taking care of Missing Data - Step 15m 56s
  • Taking care of Missing Data - Step 25m 58s
  • Encoding Categorical Data - Step 14m 24s
  • Encoding Categorical Data - Step 24m 39s
  • Encoding Categorical Data - Step 34m 24s
  • Splitting the dataset into the Training set and Test set - Step 13m 55s
  • Splitting the dataset into the Training set and Test set - Step 25m 59s
  • Splitting the dataset into the Training set and Test set - Step 33m 52s
  • Feature Scaling - Step 1-422m 36s

Logistic Regression(1h 25m)

  • Maximum Likelihood3m 43s
  • Logistic Regression in Python - Step 1-151h 12m
  • Machine Learning Regression and Classification EXTRA1m 41s
  • EXTRA CONTENT: Logistic Regression Practical Case Study59s
  • Thank You
Target student

Who Is This For?

  • Aspiring developers who want to learn the skills needed to build a successful career in software development
  • Professionals who want to expand their knowledge and stay up-to-date with the latest trends and technologies
  • Entrepreneurs who want to build their own software products
  • Students who want to supplement their formal education with practical, hands-on learning
  • Anyone who is curious about coding and wants to explore the world of software development.

Hello,

Welcome to AI Academy.

The future is already here, start with AI today to learn how to generate additional income or become one of the proffesionals in the field early.

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  • 6 comprehensive courses
  • 130 hours of HD video
  • Downloadable content
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  • Certificate of completion
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  • Learn at your own pace
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All Courses
  • 6 comprehensive courses
  • 130 hours of HD video
  • Downloadable content
  • Hands-on exercises
  • English captions
  • Certificate of completion
  • Access while subscribed
  • Learn at your own pace
Subscribe & Save

Cancel anytime!

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