The Ultimate guide to AI, Data Science & Machine Learning, Articles, Cheatsheets and Tutorials ALL in one place
Last updated 10/29/21
This is a carefully curated compendium of articles & tutorials covering all things AI, Data Science & Machine Learning for the beginner to advanced practitioner. I will be periodically updating this document with popular topics from time to time. My hope is that you find something of use and/or the content will generate ideas for you to pursue.
How to Articles: (downloadable pdf's)
Fundamentals
- How to Get a Data Science Internship
- Getting Your First Data Science Job
- END-to-END Technical Strategy for AI Engineers (118 Pages)
- Top 40 Python Interview Questions & Answers (7 pages)
- Difference between Business Intelligence & Data Science
- An example jupyter machine learning notebook
- A Practical Introduction to Prescriptive Analytics (with Case Study in R)
- DATA FALLACIES TO AVOID
- Correlation vs Causation: Definition, Differences, and Examples (6 pages)
- Machine Learning ALGORITHMS Mindmap.
- Which machine learning algorithm to use?
- Advantages Drawbacks Applications of TOP 10 algorithms (23 pages)
- How companies really leverage big data to drive performance (32 pages)
- Looking for DATASETS.
- These Are The Best Free Open Data Sources Anyone Can Use
Data Wrangling & Feature Engineering
- Step by Step Guide to Data Cleaning with Python (NumPy and Pandas)
- Feature Engineering - Getting most out of data for predictive models (76 slides)
- The Hitchhiker’s Guide to Feature Extraction (20 pages) Python
- Extracting Features from Text - A Step-by-Step NLP Guide to Learn ELMo Python
- Handling imbalanced datasets in machine learning (21 pages)
Dimension Reduction
NLP - Natural Langauge Processing - Text Analysis
Speech Analysis
Image Processing
- Setting up a Simple OCR(Optical Character Recognition) Server Python (8 pages)
- A Step-by-Step Introduction to Object Detection Algorithms (10 pages)
- Walkthrough Face Detection with Python - (20 pages)
- Scanning Images for Near-Duplicate Detection (9 pages Python)
- What Kagglers are using for Text Classification (8 pages) Python
Deep Learning
Neural Networks
Generative Adversarial Networks (GANs)
Algorithms & Techniques
- Understanding Support Vector (22 pages SVM) from examples (with code Python & R )
- Polynomial Regression As an ALTERNATIVE to Neural Nets (26 pages)
- SELF-Supervised Learning (122 pages)
- Understanding Bayesian Inference with a SIMPLE example in R (4 pages)
- Must Know Probabilistic Programming and Bayesian Methods (19 pages) Python
Clustering & Segmentation
Time Series
Visualization
Chatbots
Customer Analytics
IoT - Internet of Things
Design Thinking
Deploying / Productizing
FREE training material/courses & Notes
Cheatsheets by Topic:
Software Engineer |Open source|DPG|
2 年????Thankyou
Global, Corporate Group Head of AI at L&T Group |CTO, Sr.VP| IITB | Keynote AI Speaker | $ 27 billion, 3 startups, Entrepreneur | 26 yrs Member of Group Tech Council !| 17 yrs in AI | Gen AI Mob: 9689899815
3 年Very nice curated list, thanks Vipul Patel
Business Head at PRECIOUS COLOUR (THAI) CO LTD
3 年Awesome Knowledge bank l
Multi Cloud Solution & Devops Architect | MCT | TCS Platinum Certified Mentor | AWS Community Builder | Devops Institute Ambassador
4 年Great Collection
Head of Internal Audit at Fusion for Energy
4 年Tomorrow’s high stake for internal audit functions