data science

Networking and Professional Development for Machine Learning Careers in the USA

In today's rapidly evolving technological landscape, machine learning has emerged as a transformative discipline, revolutionizing industries and driving innovation. As…

1 year ago

Git and GitHub for Data Scientists

In this tutorial, we will focus on the basics of Git and the version control platform GitHub. Most Data scientists…

3 years ago

Decision Tree Classification in Python

Learn Decision Tree Classification, Attribute Selection Measures, Build and Optimize Decision Tree Classifier using the Python Scikit-learn package. As a…

4 years ago

Cross-Validation in scikit-learn

Cross-validation is a statistical method used in Machine Learning for estimating the performance of models. It is very important to…

4 years ago

XGBoost Algorithm using Python

XGBoost is one of the most popular boosting algorithms. It is well known to arrive at better solutions as compared…

4 years ago

Outlier Detection using Isolation Forests

For a dataset, an outlier is a data point that behaves differently from the other data points. Outliers cause huge…

4 years ago

Introduction to Ensemble Techniques: Bagging and Boosting

Ensemble Techniques are Machine Learning techniques that combine predictions from several models to give an optimal model. Several models are…

4 years ago

Introduction to Cluster Analysis

Classification of objects or cases into groups is one of the most significant concepts in Data Science and Machine Learning.…

4 years ago

Data Visualization using Seaborn

Seaborn is a Python library built on top of matplotlib. Seaborn is basically a Data Visualization library with a wide…

4 years ago

Data Science Interview Questions Part-5 (Data Preprocessing)

Top-15 frequently asked data science interview questions and answers on Data preprocessing for fresher and experienced Data Scientist, Data analyst,…

4 years ago