Here is a list of most popular blogs on machine learning plus.
Learning and Career Advice
- Why learn the math behind Machine Learning and AI?
- Mistakes programmers make when starting machine learning
- Partial Correlation
- Chi-Square test – How to test statistical significance for categorical data?
- Gentle Introduction to Markov Chain
- What is P-Value? – Understanding the meaning, math and methods
- How to implement statistical significance tests and find the p value?
- Mahalanobis Distance – Understanding the math with examples (python)
- T Test (Students T Test) – Understanding the math and how it works
- Confidence Interval in Statistics – Formula and Full Calculation
- Standard Error in Statistics – Understanding the concept, formula and how to calculate
- One Sample T Test – Clearly Explained with Examples
- Time Series Analysis in Python – A Comprehensive Guide with Examples
- ARIMA Model – Complete Guide to Time Series Forecasting in Python
- Vector Autoregression (VAR) – Comprehensive Guide with Examples in Python
- Augmented Dickey Fuller Test (ADF Test) – Must Read Guide
- Granger Causality Test
- KPSS Test for Stationarity
- Machine Learning Use Cases – The Big List of Real World Applications by Vertical and Industry
- Main Pitfalls in Machine Learning Projects
- Deploy ML in AWS Ec2 – How to Deploy ML models in AWS
- Feature selection using FRUFS and VevestaX
- Simulated Annealing Algorithm Explained from Scratch (Python)
- Bias Variance Tradeoff – Clearly Explained
- Complete Introduction to Linear Regression in R
- Logistic Regression – A Complete Tutorial With Examples in R
- Caret Package – A Practical Guide to Machine Learning in R
- Principal Component Analysis – How PCA algorithms works, the concept, math and implementation
- K-Means Clustering Algorithm from Scratch
- How Naive Bayes Algorithm Works? (with example and full code)
- Feature Selection – Ten Effective Techniques with Examples
- Evaluation Metrics for Classification Models – How to measure performance of machine learning models
- Brier Score – How to measure accuracy of probablistic predictions
- Portfolio Optimization with Python using Efficient Frontier with Practical Examples
- Gradient Boosting – A Concise Introduction from Scratch
- Setup Python environment for ML
Natural Language Processing (NLP)
- Complete Guide to Natural Language Processing (NLP) – with Practical Examples
- Text Summarization Approaches for NLP – Practical Guide with Generative Examples
- 101 NLP Exercises
- Gensim Tutorial – A Complete Beginners Guide
- LDA in Python – How to grid search best topic models?
- Topic Modeling with Gensim (Python)
- Lemmatization Approaches with Examples in Python
- Topic modeling visualization – How to present the results of LDA models?
- Cosine Similarity – Understanding the math and how it works (with python codes)
- spaCy Tutorial – Complete Writeup
- Training Custom NER models in SpaCy to auto-detect named entities [Complete Guide]
- Building chatbot with Rasa and spaCy
- SpaCy Text Classification – How to Train Text Classification Model in spaCy (Solved Example)?
- TensorFlow vs PyTorch – A Detailed Comparison
- How to use tf.function to speed up Python code in Tensorflow
- How to implement Linear Regression in TensorFlow
- How to deal with Big Data in Python for ML Projects
- Decorators in Python – How to enhance functions without changing the code?
- Generators in Python – How to lazily return values only when needed and save memory?
- Iterators in Python – What are Iterators and Iterables?
- Modules and packages in python
- Object Oriented Programming (OOPS) in Python
- Conda create environment and everything you need to know to manage conda virtual environment
- List Comprehensions in Python – Simple Guide
- Parallel Processing in Python – A Practical Guide with Examples
- Python @Property Explained – How to Use and When? (Full Examples)
- pdb – How to use Python debugger
- Python Regular Expressions Tutorial and Examples: A Simplified Guide
- Python Logging – Simplest Guide with Full Code and Examples
- datetime in Python – Simplified Guide with Clear Examples
- Requests in Python (Guide)
- Python JSON – Simple Guide
- Python Collections – An Introductory Guide
- cProfile – How to profile your python code
- Python Yield – What does the yield keyword do?
- Lambda Function in Python – How and When to use?
- What does Python Global Interpreter Lock – (GIL) do?
- Matplotlib Tutorial – Principles of creating any plot with the Matplotlib library
- Matplotlib Histogram – How to Visualize Distributions in Python
- Bar Plot in Python – How to compare Groups visually
- Boxplots in Python – How to create and interpret boxplots (also find outliers and summarize distributions)
- Waterfall Plot in Python – How to create waterfall plots for business presentations
- Top 50 matplotlib Visualizations – The Master Plots (with full python code)
- Matplotlib Tutorial – A Complete Guide to Python Plot with Examples
- Matplotlib Pyplot – How to import matplotlib in Python and create different plots
- Python Scatter Plot – How to visualize relationship between two numeric features
- Matplotlib Line Plot – How to create a line plot to visualize the trend?
- Matplotlib Subplots – How to create multiple plots in same figure in Python?
- Julia – Programming Language
- Linear Regression in Julia
- Logistic Regression in Julia – Practical Guide with Examples
- For-Loop in Julia
- While-loop in Julia
- Function in Julia
- DataFrames in Julia
- 101 NumPy Exercises for Data Analysis (Python)
- 101 Pandas Exercises for Data Analysis
- Dask – How to handle large dataframes in python using parallel computing
- Modin – How to speedup pandas by changing one line of code
- Numpy Tutorial – Your first numpy guide to build python coding foundations
- data.table in R – The Complete Beginners Guide
- 101 Python datatable Exercises (pydatatable)
- 101 R data.table Exercises
- 101 NLP Exercises (using modern libraries)