Author: Nilesh Kumar

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I am Nilesh Kumar, a graduate student at the Department of Biology, UAB under the mentorship of Dr. Shahid Mukhtar. I joined UAB in Spring 2018 and working on Network Biology. My research interests are Network modeling, Mathematical modeling, Game theory, Artificial Intelligence and their application in Systems Biology. I graduated with master’s degree “Master of Technology, Information Technology (Specialization in Bioinformatics)” in 2015 from Indian Institute of Information Technology Allahabad, India with GATE scholarship. My Master’s thesis was entitled “Mirtron Prediction through machine learning approach”. I worked as a research fellow at The International Centre for Genetic Engineering and Biotechnology, New Delhi for two years.

R k-means clustering and evaluation of the model

The k-means clustering algorithms aim at partitioning n observations into a fixed number of k clusters. The algorithm will find homogeneous clusters. It works...

Regression using Tensorflow and multiple distinctive attributes

As we did in the previous tutorial will use Gradient descent optimization algorithm. Additionally, we will divide our data set into three slices, Training,...

Regression using Tensorflow and partition of data for robust validation.

Again in the tutorial will use Gradient descent optimization algorithm. Additionally, we will divide our data set into three slices, Training, Testing, and validation....

Regression using Tensorflow and Gradient descent optimizer

Gradient descent is the most popular optimization algorithm, used in machine learning and deep learning. Gradient descent is iterative optimization algorithm for finding the...

Tensors: The building block of TensorFlow

TensorFlow uses tensor to define the framework and processing data. A tensor conceptualized multidimensions vectors and matrices. Mathematically, a tensor is a geometric object that maps...

Introduction to Boosting Machine Learning Algorithm: AdaBoost

AdaBoost algorithm Boosting is a supervised machine learning algorithm for primarily handling data which have outlier and variance. Recently, boosting algorithms gained enormous popularity in...

Algorithms Every Machine Learning Expert Should Know

This post is all about the most popular machine learning algorithms. Before we start regardless of field, it advisable to list all available tools and techniques in...

Jump headfirst into the machine learning

At present, the technology is evolving with focused on convenience; machines are being designed in a way that they can communicate with human beings...

Programming languages for Machine learning : R

From C++ to C– we have (in 2018) more than 250 programming languages and many more will emerge but which one is best suited...

Programming languages for Machine learning : Julia

From C++ to C-- we have more than 250 programming languages but which one is best suited for machine learning? There’s plenty of articles...

Azure Machine Learning: The Future of Machine Learning in the Cloud

Microsoft Azure is a Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) solution created by Microsoft. Well, these days almost every next person...

Built Artificial Neural Network in Three Lines using Sklearn

In the tutorial, we learn how to built ANN using Sklearn python library. For this example, we classify input data as an array of...

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