Artificial intelligence

Protein Structure determination aided by Stochastic Search (Replica Exchange Monte-Carlo Method)

Introduction Proteins are large molecules, which occur in abundance in every single living organism. They carryout vital functions such as transporting oxygen, converting the food you eat into energy your body can use, and many more. Proteins are long chains of linked units called amino acids. There are 20 types of amino acids. Proteins fold into different shapes depending upon their sequence of amino acids. Continue Reading

MachineX: The alphabets of Artificial Neural Network – (Part 2)

If you are reading this blog, it is supposed that you have already done with Part 1 No???? Then visit to the previous blog The alphabets of Artificial Neural Network first and comeback here for an awesome knowledge about Neural network working. We got the basic understanding of neural network so let’s get into deep. Let’s understand how neural networks work. Once you got the Continue Reading

MachineX: The alphabets of Artificial Neural Network

In this blog, we will talk about Neural network which is the base of deep learning which gave machine learning and ultra edge in the current AI revolution. Let’s get started!!!!!! before diving into deep learning, let’s know – Why Deep Learning ??? Well, there are plenty of reason , few of them are: Deep learning is most popular than shallow level learning once you Continue Reading


Knoldus Joins Clutch’s Research of Top AI & Big Data Companies in 2018

The advent of the digital economy is a development that has changed the landscapes of every industry across the world. There is a new key ingredient for success; the best performing businesses are those with the best digital platforms, built to drive performance and bring customer interaction to new heights. At Knoldus, we are a team of developers and innovators dedicated to helping businesses reach Continue Reading


Naive Bayes is a simple technique for constructing classifiers: models that assign class labels to problem instances, represented as vectors of feature values, where the class labels are drawn from some finite set. Naive Bayes classifier is a straightforward and powerful algorithm for the classification task. Even if we are working on a data set with millions of records with some attributes, it is suggested to try Continue Reading

MachineX: Logistic Regression with KSAI

Logistic Regression, a predictive analysis, is mostly used with binary variables for classification and can be extended to use with multiple classes as results also. We have already studied the algorithm in deep with this blog. Today we will be using KSAI library to build our logistic regression model. Setup

MachineX: A tour to KSAI – Neural Networks

In this blog we would look into how we can use KSAI; A machine learning library purely written in Scala using most of its feature and functional aspects of programming, you can read more about the library at KSAI Wiki, alternatively you can even fork the project from here, KSAI has a rich set of algorithms that address some of the vital problems in classification, Continue Reading

MachineX: An Introduction to KSAI, a machine learning library

Take a closer look at Linkedin or any media platform for a couple of minutes, you’ll find that the hot topic in the technology section nowadays is Machine Learning and Artificial Intelligence. Why Machine learning and artificial intelligence? Well needless to say it is transforming the world like anything. People are doing good in business by predicting different aspects, doctors are doing good in medical Continue Reading


Hi all, Knoldus has organized a 30 min session on 27th April 2018 at 4:00 PM. The topic was NAIVE BAYES CLASSIFIER. Many people have joined and enjoyed the session. I am going to share the slides here. Please let me know if you have any question related to linked slides.

KnolX: Machine Learning with Artificial Neural Networks

Hi all, Knoldus has organized a 30 min session on 8th December 2017 at 4:15 PM. The topic was Machine Learning with Artificial Neural Networks. Many people have joined and enjoyed the session. I am going to share the slides here. Please let me know if you have any question related to linked slides.   Machine Learning with Artificial Neural Networks from Knoldus Inc. Here’s the video of the Continue Reading

MachineX: Total Support Tree for Association Rule Generation

In our previous blogs on Association Rule Learning, we have seen the FP-Tree and the FP-Growth algorithm. We also generated the frequent itemsets using FP-Growth. But a problem arises when we try to mine the association rules out of these frequent itemsets. Generally, the number of frequent itemsets is massive and to run an algorithm on them becomes very memory inefficient. So, to store these Continue Reading

MachineX: Frequent Itemset generation with the FP-Growth algorithm

In our previous blog, MachineX: Understanding FP-Tree construction, we discussed the FP-Tree and its construction. In this blog, we will be discussing the FP-Growth algorithm, which uses FP-Tree to extract frequent itemsets in the given dataset. FP-growth is an algorithm that generates frequent itemsets from an FP-tree by exploring the tree in a bottom-up fashion. We will be picking up the example we used in Continue Reading

MachineX: Understanding FP-Tree construction

In my previous blog, MachineX: Why no one uses apriori algorithm for association rule learning?, we discussed one of the first algorithms in association rule learning, apriori algorithm. Although even after being so simple and clear, it has some weaknesses as discussed in the above-mentioned blog. A significant improvement over the apriori algorithm is FP-Growth algorithm. To understand how FP-Growth algorithm helps in finding frequent Continue Reading

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