Transfer learning & The art of using Pre-trained Models in Deep Learning
Introduction Neural networks are a different breed of models compared to the supervised machine learning algorithms. Why do I say so? There are multiple …
parameter tuning
Practical guide to implement machine learning with CARET package in R (with practice problem)
Introduction One of the biggest challenge beginners in machine learning face is which algorithms to learn and focus on. In case of R, the …
Tutorial: Optimizing Neural Networks using Keras (with Image recognition case study)
Introduction In my previous article, I discussed the implementation of neural networks using TensorFlow. Continuing the series of articles on neural network libraries, I have …
Winning Solutions of DYD Competition – R and XGBoost Ruled
Introduction It’s all about an extra mile one is willing to walk! Winning a data science competition require 2 things: Persistence and Willingness to try …
Complete Guide to Parameter Tuning in Gradient Boosting (GBM) in Python
Introduction If you have been using GBM as a ‘black box’ till now, may be it’s time for you to open it and see, …
Tuning the parameters of your Random Forest model
Why to tune Machine Learning Algorithms? A month back, I participated in a Kaggle competition called TFI. I started with my first submission at 50th …
