6. Pandas : apply function, handling missing values, map function for dataframes

16. Neural style transfer (Part 1 - Introduction)

15. Generative Adversarial Networks (Part 2- Training Generative Adversarial Network on Tensorflow)

14. Generative Adversarial Networks - GAN (Part 1 - Introduction)

13. Google's deep dream algorithm (Part 4- Concluding remarks)

10. Google's deep dream algorithm (Part 1 - Introduction)

12. Google's deep dream algorithm (Part 3 - Deep dream algorithm demo on tensorflow)

10. Multiclass classification on Iris dataset. Finding the best network size and universal workflow

7. Boston housing price prediction using Regression - A machine learning example

6. Binary classification of IMDB Reviews dataset in tensorflow: A machine learning example

4. Generative AI: Using LSTM to generate text, Visualizing CNN channels outputs

7. Using RNN and LSTM for NLP and timeseries forecasting

6. Using word embeddings in tensorflow and introduction to RNN

1. Understanding and implementing mathematical operations using Python for absolute beginners

7. Working on kaggle datasets and kernels

1. Object Oriented Programming using Python

4. Polymorphism in Python. Implementing design patterns in Python

3. Understanding Inheritance in python - Pillars of Object Oriented Programming

2. Complete Implementation of Encapsulation using Python

8. NoSQL Database - A practical demonstration of NoSQL on MongoDB

6. SQL Lite connectivity and Web Scrapping in Python

5. Structured Query Language (SQL) - Complete Introduction

3. How to write for loops, List comprehension, Set and dictionary in python?

8. Exception Handling in python - Understanding the usage of try, except, else and finally

9. Reading CSV/ json files in python , Certification Exam 98-381 and 17 questions with answers