Podcasts - Stories from Data and AI Practitioners
What to expect: Authentic conversations with data professionals sharing their journeys, challenges, and insights. No scripts, no sales pitches - just genuine stories that inspire and educate.
Perfect for: Anyone curious about data careers, looking for motivation, or wanting to learn from others' experiences.
Listen Anywhere
Webinars - Deep Dive Technical Sessions
What to expect: Expert-led presentations on cutting-edge data topics. Interactive sessions where you can ask questions and engage with speakers in real-time.
Perfect for: Data professionals wanting to stay current with industry trends and learn new technical skills.
📚 Complete Webinar Library
Framework(s) For Business Use-Cases
Google ML Problem Framing
ML Canvas
DL Canvas
AI Class Demonstrations
AI Demos - Tensorflow.js
AI Demos - Archived Keras.js demos
AI Demos - Google
AI Demos - Microsoft
Pix2Pix Demo
Deep Fake
Low To No Code Activities
Machine Learning Playground
Tensorflow Playground
Visualization of Convolutional Neural Networks
Convnetjs MNIST Demo
Google AI Experiments
Open Source Tooling
Open Source Ready To Go Toolkit For MLOps Arechitecture
Interview Preparation Kit
General Algorithms and Data Structures - HackerRank
Python for Data Science/ Machine Learning
Machine Learning / Deep Learning Algorithms
Useful Coding Cheatsheets
R for statistical reference
Python for Machine/Deep Learning
Productivity Tools
Notes / Project Management
Cloud-Based Website Creation
Cloud Reference Architectures
Google Cloud Platform
Python Notebooks
1. Python Fundamentals
2. Data Structures
3. Statistics
* This section presents all the Jupyter annotated notebooks related to Distribution_Functions