Artificial intelligence

KnolX: NAIVE BAYES CLASSIFIER

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

MachineX: Why no one uses apriori algorithm for association rule learning?

In my previous blog, MachineX: Two parts of Association Rule Learning, we discussed that there are two parts in performing association rule learning, namely, frequent itemset generation and rule generation. In this blog, we are going to talk about one of the algorithms for frequent itemset generation, viz., Apriori algorithm. The Apriori Principle Apriori algorithm uses the support measure to eliminate the itemsets with low Continue Reading

MachineX: Two parts of Association Rule Learning

In our previous blog, MachineX: Layman guide to Association Rule Learning, we discussed what Association rule learning is all about. And as you can already tell, with a large dataset, which almost every market has, finding association rules isn’t very easy. For these, purposes, we introduced measures of interestingness, which were support, confidence and lift. Support tells us how frequent an itemset is in a given dataset and confidence Continue Reading

MachineX: Choosing Support Vector Machine over other classifiers

When one has to select the best classifier from all the good options, often he would be on the horns of a dilemma. Decision tree/Random Forest, ANN, KNN, Logistic regression etc. are some options that often used for the choice of classification. Every one of it has its pros and cons and when to select the best one the probably the most important thing to Continue Reading

What is Deep Learning??

This term “Deep Learning”, is on fire for past two decades. Every machine learning enthusiast wants to work on it and many big companies are already making an impact on Data Science field by exploring it e.g. Google Brain project from Google or DeepFace from Facebook. The reason is simple, experts say and I quote “for most flavors of the old generations of learning algorithms … performance will Continue Reading

IoT with the AI: Why do we need this?

Artificial Intelligence (AI) and the Internet of Things (IoT) are the next level technologies and these are getting more popular in the present time. AI makes the machine to learn from its experiences and manage with new data. AI is not a new technology but due to heavy use of big data, it is now gaining again. Similarly, IoT is the combination of more than Continue Reading

Artificial Intelligence vs Machine Learning vs Deep Learning

The world as we know it is moving towards machines big time. But we can not fully utilize the working of any machine without a lot of human interaction. So in order to do that, we needed some kind of intelligence for the machines. Here comes the place for Artificial Intelligence. It is the concept of machines being smart to carry out numerous tasks without Continue Reading

Getting started with TensorFlow: A Brief Introduction

TensorFlow is an open source software library, provided by Google, mainly for deep learning, machine learning and numerical computation using data flow graphs. Looking at their website, the first definition they have written for TensorFlow goes something like this – TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges Continue Reading

First interaction Artificial Neural Network

I hated biology in my school days and loved mathematics. After a long period of time I get to learn something which combines both mathematics and biology together, that is Artificial Neural Network short for ANN, inspired by biological Neural network. Though you might find it weird, that is how I would like to define the artificial neural network. When we say biology here, it Continue Reading

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