# How to create tensorflow tfrecords out of any dataset:

## A complete step by step tutorial for absolute beginners with example

When working with deep learning models, we often use very large datasets. It can be very useful to store them in a binary file format that takes up less space and so improve training time. The TFRecord format is a simple format in tensorflow for storing a sequence of binary…

# A Gentle Introduction to Backpropagation and Implementing Neural Network Animation

At its core, a neural network is an algorithm that was designed to learn patterns in real-life data and make predictions. An important part of this learning is done using the backpropagation algorithm. The backpropagation attempts to correct errors at each layer to make a better prediction. We can do…

# Activation Functions:

When you build a neural network, one of the decisions you can make is the choice of an activation function. Activation functions give neural networks the power of mapping nonlinear functions. Imparting non-linearity to the neural network helps it to solve complex problems. They help your model to capture squiggly…

# Understanding Gradient Descent and breaking down the math behind:

Gradient descent is a widely used optimization algorithm used by a range of machine learning algorithms. Machine learning algorithms have cost functions that compute the error (predicted value — actual value) of the model. So, the best model has to be the one that has the minimum cost. The goal…

# Understanding Adaboost and Scikit-learn’s algorithm:

Ensemble models and more particularly Boosting algorithms have become quite popular on online data science competition forums like Kaggle. Ensemble learning is the method of using a group of models to make our prediction. Today we are going to talk about an ensemble boosting algorithm called AdaBoost. If you aren’t…

# Ensemble Learning Methods in Machine Learning

Ensemble learning is a compelling technique that helps machine learning systems improve their performance. The technique gained a lot of popularity in the online data science competition platform Kaggle with a good number of winning solutions using ensembling methods. It uses a group of models to predict rather than just…

# Logistic Regression: Understand the math behind the algorithm

Logistic regression is a supervised binary classification algorithm. You’re probably wondering why its called logistic regression then, it's only because it uses the concept of regression to classify. If that doesn’t make sense to you yet, don't worry, we’re going to break it all down. In logistic regression, the target…

# Types of Distance Metrics and Using User Defined Distance metrics in Scikit’s KNN Algorithm:

KNN algorithm is one of the most commonly used and important algorithms in data science. It is a supervised classification algorithm, meaning that the data we feed into the algorithm is labeled and we use them to classify the data based on their similarities. The algorithm works by first measuring… 