Course Overview

This learning path is the perfect destination for you. Here, you'll master the basics of machine learning and AI, while you'll also gain practical training on how to apply these technologies to business problems. You'll learn data mining techniques, and you'll also learn to build custom object detector models using Deep Learning. The learning path will provide a hands-on understanding of unsupervised learning and natural language processing.

What You Will Learn

  • Explore the most advanced Machine Learning techniques and their use cases
  • Master linear algebra & modeling.
  • Understand data Mining techniques and their practical uses
  • Learn about Deep Learning.
  • Learn about object detection models and data collection & annotation.
  • Get equipped with principal component analysis and its use in daily tasks
  • Learn how to do the face alignment using MTCNN face detection
  • Learn about Emotion Detection

Program Curriculum

Content
  • Chapter 1: Set up the Environment
  • Chapter 2: Jupyter Notebook Coding Environment
  • Chapter 3: Image Process
  • Chapter 4: Classification Model Explanation
  • Chapter 5: TensorFlow Introduction and Quick Guide
  • Chapter 6: Write a Classification Class Program
  • Chapter

Content
  • Chapter 1: Overview of Course
  • Chapter 2: Essential of Deep Learning
  • Chapter 3: Introduction to CNN
  • Chapter 4: Deep Dive into CNN
  • Chapter 5: Activation Function & Gradient Descent
  • Chapter 6: Hands-on with CNN
  • Chapter 7: In-depth with Autoencoders
  • Chapter 8:

Content
  • Chapter 1: Introduction
  • Chapter 2: Principal Component Analysis
  • Chapter 3: t-SNE
  • Chapter 4: Autoencoders
  • Chapter 5: Restricted Boltzmann Machines
  • Chapter 6: Latent Semantic Analysis
  • Chapter 7: Recommender System

Content
  • Chapter 1: Overview of Course
  • Chapter 2: Data Collection and Annotation
  • Chapter 3: Introduction to YOLO
  • Chapter 4: Mathematics behind YOLO
  • Chapter 5: Essentials of Model Training
  • Chapter 6: Train Your Custom Object Detection
  • Chapter 7: Test your Model

Content

Chapter 1: Introduction to Face Recogn

Content

Content

Content

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Instructor

Vivek Chaudhary chaudhary

Vivek Chaudhary currently works as a freelance data scientist and has worked with different product-based & EdTech startups. He has published one of the best-selling books on Amazon, �Data Investigation-EDA the right way�. His areas of expertise are applied statistics, EDA, data cleaning techniques, and feature engineering and process to building statistical models. According to him �Building Assumptions� is the important factor to apply statistical tools in real-time. If you can�t build assumptions, then no matter how much you learn at the end, it will be difficult to apply statistical techniques. He has mentored 200+ professionals to start their journey and helped them understand applied statistics & EDA.

Vivek Chaudhary chaudhary

Vivek Chaudhary currently works as a freelance data scientist and has worked with different product-based & EdTech startups. He has published one of the best-selling books on Amazon, �Data Investigation-EDA the right way�. His areas of expertise are applied statistics, EDA, data cleaning t

Vivek Chaudhary chaudhary

Vivek Chaudhary chaudhary

Abhilash Nelson

Yuan Po Liao

Wassim Ben Youssef

Aashish Dixit

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Practical Artificial Intelligence for Professionals

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