#Machine Learning

Build your first ML project

Let’s build your first machine learning project with Python from scratch. “But I am a complete beginner, I am not ready yet!..” – Your...

Setup Python environment for ML

Python is the most popular programming language used for AI and machine learning. Let’s see how to setup python environment for ML using anaconda....

Train Test Split – How to split data into train and test for validating machine learning models?

The train-test split technique is a way of evaluating the performance of machine learning models. Whenever you build machine learning models, you will be...

Data Science Roadmap – How to become a Data Scientist? (6 month self study plan)

Today, I discuss the Data Science Roadmap, the missing guide to self study machine learning. I’ll discuss what exactly you need to know and...

Why learn the math behind Machine Learning and AI?

Why learn the math behind machine learning algorithms when you can readily implement it using the python libraries like scikit-learn, h2o, statsmodels etc? This...

Machine Learning Use Cases – The Big List of Real World Applications by Vertical and Industry

The use cases of machine learning to real world problems keeps growing as ML/AI sees increased adoption across industries. However, there are certain core...

Main Pitfalls in Machine Learning Projects

Not all Data Science projects that get kicked-off see the light of day. While this is true for any project, there are common reasons...

Regression Coefficient Formula

  Let’s understand the formula for the linear regression coefficients. That is the formula for both alpha and the beta. Now, if you have...

Nebullvm – Tutorials and benchmarks on Nebullvm, the open-source deep learning inference accelerator

Nebullvm is an open-source library that takes a deep learning model as input and outputs an optimized version that runs 5-20 times faster on...

Simulated Annealing Algorithm Explained from Scratch (Python)

ARIMA Model – Complete Guide to Time Series Forecasting in Python

Using ARIMA model, you can forecast a time series using the series past values. In this post, we build an optimal ARIMA model from...

Text Summarization Approaches for NLP – Practical Guide with Generative Examples

Text summarization in NLP is the process of summarizing the information in large texts for quicker consumption. In this article, I will walk you...

Bias Variance Tradeoff – Clearly Explained

Bias Variance Tradeoff is a design consideration when training the machine learning model. Certain algorithms inherently have a high bias and low variance and...

Logistic Regression in Julia – Practical Guide with Examples

Julia is a powerful programming language for Machine Learning and Logistic regression is one of the most popular predictive modeling algorithms, used for binary...

Confidence Interval in Statistics – Formula and Mathematical Calculation

Confidence interval is a measure to quantify the uncertainty in an estimated statistic (like the mean) when the true population parameter is unknown. Training...

Building chatbot with Rasa and spaCy

Conversational AI systems have revolutionized over the decade. Almost every company faces the requirement to use a Chat Bot. Rasa provides a smooth and...

SpaCy Text Classification – How to Train Text Classification Model in spaCy (Solved Example)?

Text Classification is the process categorizing texts into different groups. SpaCy makes custom text classification structured and convenient through the textcat component. Text classification...

How to use tf.function to speed up Python code in Tensorflow

tf.function is a decorator function provided by Tensorflow 2.0 that converts regular python code to a callable Tensorflow graph function, which is usually more...

TensorFlow vs PyTorch – A Detailed Comparison

Compare the popular deep learning frameworks: Tensorflow vs Pytorch. We will go into the details behind how TensorFlow 1.x, TensorFlow 2.0 and PyTorch compare...