Home Courses Applied Machine Learning Online Course Spark for Data Science and Machine Learning [Architecture and Programming model]- I

Spark for Data Science and Machine Learning [Architecture and Programming model]- I

Instructor: Applied AI Course

Notes:https://drive.google.com/file/d/1xyDGCltCmgsqMxaCQiifnLa3bUH-BYJd/vieww

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Big-Data & Cloud Storage for ML/AI Applications

Spark for Data Science and Machine Learning [Setup + Code walkthroughs]-II

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Machine Learning High-Level Design

1.1

Machine Learning design: Search engine for Q&A

1.2

ML System Design: Feature Store

31 min

Sample Interview and Conceptual Questions [AUDIO]

2.1

Sample Interview and Conceptual Questions [AUDIO]

Reinforcement Learning

3.1

Applications of RL

10 min

3.2

Problem Forumulation & Terminology

8 min

3.3

Bellman Equation

20 min

3.4

Dynamic Programming and RL

11 min

3.5

Markov Decision Process (MDP)

12 min

3.6

7 min

3.7

Temporal Difference

11 min

3.8

Deep Q Learning: Intuition

5 min

3.9

37 min

Module 10: Live Sessions

4.1

An overview of AI Algorithms ( a 10,000 feet view)

4.2

Introduction to Big data for ML and AI

4.3

Big-Data & Cloud Storage for ML/AI Applications

4.4

Spark for Data Science and Machine Learning [Architecture and Programming model]- I

4.5

Spark for Data Science and Machine Learning [Setup + Code walkthroughs]-II

4.6

Spark for Data Science and Machine Learning [ML Lib and ML Pipelines]-III

4.7

How to Build a Chatbot?

4.8

Design and build a Chatbot from Scratch

4.9

Design and build a Chatbot from Scratch-Part 2

4.10

How to build IoT + AI systems

4.11

LIVE: How to Crack ML Competitions

4.12

Live: Effective communication for DS and MLEs

4.13

Sample Interview and Conceptual Questions [AUDIO]

4.14

Various roles in an ML/DataScience team

13 min

4.15

Client management for AI Projects

11 min

4.16

Live Session(17th July 2022): ML System design Interview session

1 min