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Artificial intelligence

Boosting medical diagnosis with Klickare

AI, Artificial intelligence, ML, AI and Data Engineering, , ,

Reading Time: 4 minutes In this blog, we are going to see how KlicKare can boost up medical diagnosis by using deep learning. Medical diagnostics are a category of medical tests designed to detect infections, conditions, and diseases. These medical diagnostics fall under the category of in-vitro medical diagnostics (IVD) which be purchased by consumers or used in laboratory settings. Biological samples are isolated from the human body such Continue Reading

MachineX: Alphabets of PyTorch (Part 1)

AI, Artificial intelligence, ML, AI and Data Engineering, ,

Reading Time: 6 minutes Overview In this blog, you’ll get an introduction to deep learning using the PyTorch framework, we will see some basics of PyTorch. Introduction to PyTorch PyTorch is a Python machine learning package based on Torch, which is an open-source machine learning package based on the programming language Lua. Two main features: Tensor computation (like NumPy) with strong GPU acceleration Automatic differentiation for building and training Continue Reading

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

Artificial intelligence, Big Data and Fast Data, Business Insights, ,

Reading Time: 2 minutes 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

MachineX: Logistic Regression with KSAI

Artificial intelligence, ML, AI and Data Engineering, software, Studio-Scala, , , , , , , , ,

Reading Time: 2 minutes 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: An Introduction to KSAI, a machine learning library

Akka, Artificial intelligence, ML, AI and Data Engineering, Studio-Scala,

Reading Time: 3 minutes 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

KnolX: NAIVE BAYES CLASSIFIER

Artificial intelligence, ML, AI and Data Engineering, Studio-Scala, , , , , , ,

Reading Time: < 1 minute 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

Artificial intelligence, ML, AI and Data Engineering, Studio-Scala, ,

Reading Time: < 1 minute 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

Artificial intelligence, ML, AI and Data Engineering, Studio-Scala, , , , , , ,

Reading Time: 5 minutes 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

Artificial intelligence, ML, AI and Data Engineering, Studio-Scala, , , , , ,

Reading Time: 4 minutes 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

Artificial intelligence, ML, AI and Data Engineering, Studio-Scala, , , , , , , ,

Reading Time: 5 minutes 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?

Artificial intelligence, ML, AI and Data Engineering, Studio-Scala, , , , , , ,

Reading Time: 3 minutes 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

Artificial intelligence, ML, AI and Data Engineering, Studio-Scala, , , , , , , ,

Reading Time: 2 minutes 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

Artificial intelligence, ML, AI and Data Engineering, Studio-Scala, , , , ,

Reading Time: 4 minutes 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

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