AI

Blockchain Smart Contract Security

Blockchain is a digital ledger in which cryptocurrency transactions are recorded. In this article, Arjun Bahuguna discusses ethereum, a public blockchain, as it is the most popular platform for writing smart contracts and building decentralized applications.

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Quantization and the Need for TPUs

Archana dives into the world of TPUs and discusses quantization, the process that is really responsible for making predictions in a neural network, lending a magical touch to the machine learning process. Read on to understand how quantization can be both a boon and a bane, depending on where it is used.

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Analytics Trends 2018: Blockchain and AI to Accelerate Clinical Trials Transformation

All clinical trial processes are witnessing rapid transformation due to the demand for faster and completion of trials at lower costs. Insights gleaned from Real World Data (RWD) in the past few years have offered several avenues for improving clinical trials. Sagar Anisingaraju discusses the upcoming trends of 2018 in this light. Read on to learn about the technologies poised to make a wave this year.

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An Attentive Sequence Model for Adverse Drug Event Extraction from Biomedical Text

Adverse reaction caused by drugs is a potentially dangerous problem which may lead to mortality and morbidity in patients. Adverse Drug Event (ADE) extraction is a significant problem in biomedical research. We model ADE extraction as a Question-Answering problem and take inspiration from Machine Reading Comprehension (MRC) literature, to design our model. Our objective in…

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Different Kinds of Convolutional Filters

Convolutional Neural Networks have brought about huge changes in computer vision and other image related tasks. Soham Chatterjee discusses how different convolution operations work and uses illustrations of design techniques for different filters to explain them in depth.

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Applications of Signal Processing in Machine Learning

machine learning

Data is available abundantly in today’s world. However, it is noisy most of the time. In this article, Archana Iyer discusses some filter processing techniques that can help us get a better quality of data. With the advent of IoT, many types of medical data are now available in the form of sensor data. This…

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Capsule Networks and the Limitations of CNNs

machine learning

Convolutional Neural Networks are considered the State-of-the-Art in computer vision related Machine Learning tasks. Soham Chatterjee highlights the limitations of CNNs and discusses alternate models that closely mirror the way the human brain work. He uses Professor Geoffrey Hinton’s paper, Dynamic Routing Between Capsules, to establish certain points. Convolutional Neural Networks, popularly called CNNs, have…

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Deep Learning Diaries: Building Custom Layers in Keras

Deep Learning

There are many deep learning libraries available, some are more popular than the others, and some get used for very specific tasks.  Abhai Kollara discusses the merits of Keras and walks us through various examples of its uses and functionalities. He also compares it with some of the popular libraries. Natural Language Processing or Computer…

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New Frontiers in Data Analytics for Pharma and Healthcare

Data Analytics

Mining Unstructured Texts for Insights using Convolutional Neural Networks Pharmaceutical and Healthcare domains deal with a tremendous amount of unstructured texts, which can be mined effectively using CNN for NLP approach. Malaikannan Sankarasubbu talk about these advanced techniques that can have many applications, such as, building better cohort for clinical trials or establishing better inclusion/exclusion…

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