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🌏World roaming Software Technology Evangelist. Proud Indian, Bought up from Coimbatore, Tamilnadu, INDIA. Pointing towards share of Knowledge. 😎
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Referred Link -
https://www.linkedin.com/pulse/all-cheatsheets-one-place-vipul-patel/




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
The Ultimate Guide to 12 Dimension Reduction Techniques (20 pages) Python

NLP - Natural Langauge Processing - Text Analysis
Practical Introduction to Web Scraping in Python
A Step-by-Step Guide for Building a Tweet Classifier with Python - (14 pages)
Walkthrough Example Implement Text Classification with Python - (14 pages)
Walkthrough Sentiment Analysis - Model for Predicting Review Sentiment in Python

Speech Analysis
The Ultimate Guide To Speech Recognition with Python

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
Walkthrough how to use Deep Learning to solve a problem with Python - (13 pages)
A Comprehensive Hands-on Guide to Transfer Learning with Real-World Applications in Deep Learning

Neural Networks
How To Create Your first ANN - Artificial Neural Network In Python (7pages)
Build an RNN - Recurrent Neural Network from Scratch in Python (11 pages)
CNNs, Part 1: An Introduction to Convolutional Neural Networks

Generative Adversarial Networks (GANs)
GANs from Scratch 1: A deep introduction. PyTorch & TensorFlow code (25 pages)

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
Comparison of Segmentation Approaches using Clustering (9 pages)
Guide to HIERARCHICAL Clustering (23 pages) and how to Perform it in Python

Time Series
Extensive Time series analysis tutorial in Python (56 pages)

Visualization
3 Awesome Visualization Techniques for every dataset in Python
Data Visualization in R - (62 pages)
Data Visualization in Python - (7 pages)
The Data Visualisation Catalogue

Chatbots
Build your first chatbot in Python using NLTK - (6 pages)

Customer Analytics
Recommend the Best Channels for Contact Python (9 pages)

IoT - Internet of Things
Four Options for Integrating Machine Learning with IoT

Design Thinking
What is Design Thinking and Why Is It So Popular?

Deploying / Productizing
Deploying a Python Web App on AWS

FREE training material/courses & Notes
A Facebook field guide to Machine Learning - Video Series
Essential Notes (28 Pages) - Coursera Deep Learning Course by Andrew Ng

Cheatsheets by Topic:
Artificial Intelligence
Big Data Analytics
Big Data
Data Engineering
Data Engineering (Google)
Data Mining
Data Science
Data Visualization
Data Visualization (Python)
Data Warehouse
Deep Learning
Visual Explanation of Deep Learning (21 pages)
DevOps
Docker & Kubernetes
Excel
GIT
Interview Questions
Linux
Machine Learning
Machine Learning Infographic with code
Mathematics
Matlab
Model Building Process Flowchart
Ordinary Differential Equations
Probability
Python
R Cheat Sheet
Segmentation & Clustering Cheatsheet for R & Python
SQL
SQL (Graphical)
Scala
Statistics

Tags:
#opensource #data #cheatsheet #tutorial #learning #guide   #ml #ai #machinelearning  #artificialintelligence  #datascience #deeplearning  #predictiveanalytics #featureengineering #NLP #GAN #CNN #RNN #clustering #segmentation #visualization #visualisation #SVM #datamining #textmining #python #R #scala 


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Jay Srinivasan
Professional: I'm a Software Techie, Specialized in Microsoft technologies. Worked in CMM Level 5 organizations like EPAM, KPMG, Bosch, Honeywell, ValueLabs, Capgemini and HCL. I have done freelancing. My interests are Software Development, Graphics design and Photography.
Certifications: I hold PMP, SAFe 6, CSPO, CSM, Six Sigma Green Belt, Microsoft and CCNA Certifications.
Academic: All my schooling life was spent in Coimbatore and I have good friends for life. I completed my post graduate in computers(MCA). Plus a lot of self learning, inspirations and perspiration are the ingredients of the person what i am now.
Personal Life: I am a simple person and proud son of Coimbatore. I studied and grew up there. I lost my father at young age. My mom and wife are proud home-makers and greatest cook on earth. My kiddo in her junior school.
Finally: I am a film buff and like to travel a lot. I visited 3 countries - United States of America, Norway and United Kingdom. I believe in honesty after learning a lot of lessons the hard way around. I love to read books & articles, Definitely not journals. :)
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