CPG

Attention Mechanism: Benefits and Applications

Recurrent Neural Networks (RNNs) are powerful neural network architectures used for modeling sequences. LSTM (Long Short Term Memory) based RNNs are surprisingly good at capturing long-term dependencies in the sequences. A barebones sequence-to-sequence/encoder-decoder architecture performs incredibly well in tasks like Machine Translation. A typical sequence-sequence architecture consists of an encoder and a decoder RNN. The…

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Women and Data Science

It is well-known that there are far fewer women techies and those that do choose work in tech, somehow avoid data science. Archana Iyer discusses the merits of having more women in the field of data science and presents some reasons why she feels that women’s innate temperament is highly suited to data science.

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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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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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