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Deep Learning for Computer Vision – Introduction to Convolution Neural Networks
A tutorial for convolution neural networks to identify images. Learn about deep learning for computer vision and implement CNNs using graphlab in python.
Aarshay Jain 05 Jul, 2020
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13 Machine Learning & Data Science Startups from Y Combinator Winter 2016
This article presents the machine learning, data science startups from Y Combinator winter batch 2016. These startups use data and analytics
Analytics Vidhya 23 Jul, 2019
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Practical Guide to Deal with Imbalanced Classification Problems in R
Learn about the challenges of imbalanced classification in R and how it can affect the accuracy of machine learning algorithms. Read Now!
Analytics Vidhya 04 Nov, 2024
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Exploring Recommendation System (with an implementation model in R)
This tutorial illustrates use of recommendation engines in the banking industry with practicals done in R. It also explains types of recommendation engines.
Tavish Srivastava 05 Jul, 2020
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How to perform feature selection (i.e. pick important variables) using Boruta Package in R ?
Boruta package is a wrapper algorithm around random forest for important variables and used to perform feature selection in R for data science.
Guest Blog 26 Aug, 2021
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Winning Solutions of DYD Competition – R and XGBoost Ruled
This article reveals the winning solutions of date your data competition. Winners used R, python and boosting algorithms to get winning scores
Analytics Vidhya 18 Mar, 2016
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Fundamentals of Deep Learning – Starting with Artificial Neural Network
This article explains artificial neural networks and fundamentals of deep learning. Learn about forward and backward propagation.
Aarshay Jain 14 Jun, 2023
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Complete Solution: How I got in Top 11% of Kaggle Telstra Competition ?
This is a complete solution of machine learning data mining competition Kaggle Telstra network disruption competition using xgboost ensemble
Aarshay Jain 02 Aug, 2019
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Tutorial on 5 Powerful R Packages used for imputing missing values
Learn about powerful R packages like amelia, missForest, hmisc, mi and mice used for imputing missing values in R for predictive modeling in data science.
Analytics Vidhya 05 Jul, 2020
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XGBoost Parameters Tuning
Explore XGBoost parameters and hyperparameter tuning like learning rate, depth of trees, regularization, etc. to improve model accuracy.
Aarshay Jain 03 Dec, 2025
