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

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.

Abhilash Nelson

Abhilash Nelson is a pioneering, talented and security-oriented Android/iOS Mobile and PHP/Python Web Developer Application Developer offering more than eight years’ overall IT experience which involves designing, implementing, integrating, testing and supporting impact-full web and mobile applications. He is a Postgraduate Master's Degree holder in Computer Science and Engineering and is currently serving full time as a Senior Solution Architect managing my client's projects from start to finish to ensure high quality, innovative and functional design.

Yuan Po Liao

Johnny has an MS in electrical engineering from National Central University in Taiwan. He used to be a cellphone hardware engineer in the Hon Hai Technology Group. For the interest of coding, he learned C and Python by self-study. He completed IOT Wifi and Zigbee systems applied in TSMC, Arcadyan, Delta, Mitac, and ITRI. With the explosive growth of AI, he learned AI basics by self-study. He has been a full-time AI computer vision engineer since he left his previous firmware system engineer job several years ago.

Wassim Ben Youssef

Wassim Ben Youssef has 4 years of experience in Data Science and applied Machine Learning. He has worked as a Data Scientist for several fintech startups in London, helping them to build their Data Science team and develop and deploy Machine Learning models into their products. He is also a teaching assistant for a company providing Data Science Bootcamps. Passionate and excited about how AI can change the world, Wassim likes to stay connected with the Data Science community and informed of the new cutting-edge applications of AI by attending events such as the Data Science Festival or CognitionX. Wassim holds several Master degrees in Data Science, Applied Mathematics and Computer Science.

Aashish Dixit

Aashish has spent a lot of his life studying and teaching. He holds a master’s and bachelor’s degree in Engineering. He has also spent a lot of his life working as a senior Network Data engineer at GE & HP in Gurgaon (& San Jose), then as a Manager Data N/W, first with JP Morgan Chase, Ohio and then on his own, and finally at Flipkart and Cisco in Bangalore. In all these roles, he has written a lot of code and built a lot of models. He has spent around two decades teaching high-quality, in-depth courses on advanced Mathematics, Data Science & Technology. I have helped hundreds of learners become champions in subjects and enabled them to change their lives, with his students working at companies such as Amazon, Google, Cisco, and Facebook.

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