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Weekly Selection

Dear readers and contributors,

Dear readers and contributors,

this week, spring has sprung, and so has our understanding of deep learning, statistics and applications of data science, thanks to our knowledgeable and erudite writers. We are delighted to present to you, our Weekly Selection of our favorite articles featured on Towards Data Science.

Our mission has always been to bring you interesting, useful articles about data science philosophy, theory and application. We want to provide top quality, trusted information that our readers can learn from, and that show case the best work our writers can produce.

March has brought some big changes at TDS. We are incredibly proud that we are currently receiving as many as 10 submissions every day, and now have a stable of over 70 contributors.

Now is the time to raise the bar.

We are looking for members of our community to help us move to the next level in terms of providing excellent articles to our readers and helping our budding writers to develop their voice through editorial assistance.

Join us as an Editorial Associate of Towards Data Science.

We look forward to reading your submissions over the coming week and we hope to welcome some Editorial Assistants to the TDS team!


Neural Network Architectures

By Eugenio Culurciello – Reading: 14 min

Deep neural networks and Deep Learning are powerful and popular algorithms. And a lot of their success lays in the careful design of the neural network architecture.


LSTM by Example using Tensorflow

By Rowel Atienza – Reading: 6 min

In Deep Learning, Recurrent Neural Networks (RNN) are a family of neural networks that excels in learning from sequential data. A class of RNN that has found practical applications is Long Short-Term Memory (LSTM) because it is robust against the problems of long-term dependency.


Glowworms, Hot Hand, and Other (Alleged) Fallacies in Data-Interpretation.

By Henry Kim – Reading: 4 min

Long time ago, when I was learning cognitive psychology for the first time, I was assigned the famous paper on the so-called "Hot Hand Fallacy." The point was simple: people are bad at evaluating probabilities.


Machines Eradicating Cancer

By Oliver Mitchell – Reading: 6 min

At the SxSw Interactive Conference in Austin this week, Former Vice President Joe Biden challenged all innovators to think BIGGER. Biden’s Cancer Moonshot Task Force , established last January, brings together 20 government agencies and more than 70 private-sector companies with one aim – "eliminate cancer as we know it."


Feature Engineering: Bayesian Methods for Binning

By Andrew Greatorex – Reading: 5 min

One of the most crucial pieces of any data science puzzle is perhaps also the least glamorous: feature engineering. It can be protracted and frustrating, but if it’s not done right, it can spell disaster for any modelling or analysis that follows.


Monte Carlo Analysis and Simulation

By Arnaldo Gunzi – Reading: 8 min

The Monte Carlo method is an simple way to solve very difficult probabilistic problems. This text is a very simple, didactic introduction to this subject, a mixture of history, mathematics and mythology.


My Name is Inigo Montoya. A Case for Empathizing with Speech Recognition Apps.

By Lucian Lita – Reading: 6 min

Hello. My name is Amigo Mongolia. Sigh. Indigo Latoya. Grrrr. Inigo Montoya. Sometimes it takes everything you’ve got to keep your cool when working with speech recognition apps. For many of us, names are the worst stressors.


Solve Slide Puzzle with Hill Climbing Search Algorithm

By Rahul Aware – Reading: 3 min

Hill climbing search algorithm is one of the simplest algorithm which falls under local search and optimization techniques. Here’s how it’s defined in ‘An Introduction to Machine Learning’ book by Miroslav Kubat.


BLOCKCHAIN VS. ARTIFICIAL INTELLIGENCE

By Boris Lavrov – Reading: 12 min

There are two major trends you can’t miss in the world of tech today. The first is the resurgence of artificial intelligence (AI) techniques: advances in computer vision, natural language processing and generation, machine translation, and processing and analytics of massive datasets.


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