Coding Interview Companion for AI and Deep Learning

Coding Interview Companion for AI and Deep Learning, available at $34.99, has an average rating of 3.5, with 66 lectures, based on 1 reviews, and has 21 subscribers.

You will learn about Coding interview for Deep Learning and Machine Learning This course is ideal for individuals who are Developers looking for job in Deep Learning and Machine Learning or University pass outs curious about Artificial Intelligence or Professionals willing to understand inner core of AI journey or Students who wants to explore and learn AI or Professors who would like to teach new ideas and core AI It is particularly useful for Developers looking for job in Deep Learning and Machine Learning or University pass outs curious about Artificial Intelligence or Professionals willing to understand inner core of AI journey or Students who wants to explore and learn AI or Professors who would like to teach new ideas and core AI.

Enroll now: Coding Interview Companion for AI and Deep Learning

Summary

Title: Coding Interview Companion for AI and Deep Learning

Price: $34.99

Average Rating: 3.5

Number of Lectures: 66

Number of Published Lectures: 51

Number of Curriculum Items: 66

Number of Published Curriculum Objects: 51

Original Price: $44.99

Quality Status: approved

Status: Live

What You Will Learn

Coding interview for Deep Learning and Machine Learning

Who Should Attend

Developers looking for job in Deep Learning and Machine Learning
University pass outs curious about Artificial Intelligence
Professionals willing to understand inner core of AI journey
Students who wants to explore and learn AI
Professors who would like to teach new ideas and core AI

Target Audiences

Developers looking for job in Deep Learning and Machine Learning
University pass outs curious about Artificial Intelligence
Professionals willing to understand inner core of AI journey
Students who wants to explore and learn AI
Professors who would like to teach new ideas and core AI

Artificial Intelligence, Deep Learning, Machine learning and Data Science are buzz words that you would hear quite often these days. These area provide good number of job opportunities and it very much essential that you understand the fundamentals concepts of these when facing an interview. This course aims to feed you with confidence to face a coding interview on Machine Learning and Deep Learning. We shall walk over 50+ interview questions with hands-on code and prepare you for the same. All of the code is written in Python and will focus to explain the concepts from scratch.

>Do you know, About half a million job openings are available across the globe. Data Science and ML engineer are the job roles with most openings

> Harvard Business Review has stated that “Data Science” as most attractive job of the 21st century.

>last but not the least The Salary bar in this domain is also quite high than regular IT professionals.

In-fact, The demand for these niche skills are 10 times more than the number of graduates passing out of the college. Given so much of background on need to adopt this skill, would you not take a shot at it ..?

I would recommend that, Whichever is your career path just club it up with AI and then accelerate . So why wait? Lets get Started.

Course Curriculum

Chapter 1: Welcome

Lecture 1: Introduction

Lecture 2: Evolution of AI

Lecture 3: Course Overview

Lecture 4: Prerequisites

Lecture 5: Tools for Coding

Chapter 2: Setting the stage

Lecture 1: Why AI ..?

Lecture 2: Statistics – Code Walkthrough

Lecture 3: Supervised Learning

Lecture 4: Machine Learning Types – Question Drive

Lecture 5: Supervised Algorithm (I) by Math – Proof of Concept

Lecture 6: Proximity – Code Walkthrough

Lecture 7: Supervised Algorithm (II) from Scratch – Code Walkthrough

Lecture 8: Data Structures & Algorithms – Code Walkthrough

Lecture 9: Data Structures & Algorithms : Driver – Code Walkthrough

Chapter 3: Image Processing and Convolutional Neural Networks

Lecture 1: Neural Networks – Visual Walkover

Lecture 2: Computing Polar Angle – Code Walkthrough

Lecture 3: Processing Orientation – Code Walkthrough

Lecture 4: Find Boundary – Question Drive

Lecture 5: Convex Hull Algorithm – Code Walkthrough

Lecture 6: Pixels & Image Processing – Code Walkthrough

Chapter 4: Natural Language Processing

Lecture 1: Natural Language Processing – Question Drive

Lecture 2: Natural Language Processing (II) – Question Drive

Lecture 3: NLP Warmup Exercise (I) – Code Walkthrough

Lecture 4: NLP Warmup Exercise (II) – Code Walkthrough

Lecture 5: NLP Words Computations – Code Walkthrough

Lecture 6: NLP Sentence Manipulations (I) – Code Walkthrough

Lecture 7: NLP Sentence Manipulations (II)- Coding Hands-on

Lecture 8: NLP Sentence Manipulations (III) – Code Walkthrough

Lecture 9: NLP Sentence Manipulations (IV) – Code Walkthrough

Lecture 10: NLP Regular Expressions (I) – Code Walkthrough

Lecture 11: NLP Regular Expressions (II) – Code Walkthrough

Lecture 12: NLP Regular Expressions (III) – Code Walkthrough

Lecture 13: NLP Paragraph Manipulation (I) – Code Walkthrough

Lecture 14: NLP Paragraph Manipulation (II) – Code Walkthrough

Lecture 15: NLP Text Pre-processing (i) – Code Walkthrough

Lecture 16: NLP Text Pre-processing (II) – Code Walkthrough

Lecture 17: NLP Text Pre-processing (III) – Code Walkthrough

Lecture 18: NLP Text Pre-processing (IV) – Code Walkthrough

Lecture 19: NLP Text Pre-processing (V) – Code Walkthrough

Lecture 20: NLP Text Pre-processing (VI) – Code Walkthrough

Lecture 21: NLP Text Pre-processing (VII) – Code Walkthrough

Lecture 22: NLP Text Pre-processing (VIII) – Code Walkthrough

Lecture 23: NLP Text Pre-processing (IX) – Code Walkthrough

Lecture 24: NLP Build Spell Checker – Code Walkthrough

Lecture 25: NLP Text Manipulation Algorithm (I) – Code Walkthrough

Lecture 26: NLP Genome Computations – Code Walkthrough

Lecture 27: NLP Text Manipulation Algorithm (II) – Code Walkthrough

Lecture 28: NLP Vectorization : Math – Question Drive

Lecture 29: NLP Bag of Words – Code Walkthrough

Lecture 30: NLP Stop Words Removal – Question Drive

Chapter 5: Conclusion

Lecture 1: Thank you & Next steps

Instructors

Vidya Ranganathan
Architect| Author | Inventor

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Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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