Author: Deep Thoughts

How to train Baidu’s Deepspeech model

You want to train a Deep Neural Network for Speech Recognition? Me too. It was two years ago and I was a particle physicist finishing a PhD at University of Michigan. I could code a little in C/C++ and Python

10 Lies Depression Tells You

Practical seq2seq

Revisiting sequence to sequence learning, with focus on implementation details Posted on December 31, 2016 In my last article, I talked a bit about the theoretical aspect of the famous Sequence to Sequence Model. I have shared the code for my

Learn to build a chatbot using TensorFlow

 Part II of Sequence to Sequence Learning is available here. Last year, Telegram released its bot API, providing an easy way for developers, to create bots by interacting with a bot, the Bot Father. Immediately people started creating abstractions in nodejs, ruby and

Deep Learning for Chatbots, Part 1 – Introduction

Chatbots, also called Conversational Agents or Dialog Systems, are a hot topic. Microsoft is making big bets on chatbots, and so are companies like Facebook (M), Apple (Siri), Google, WeChat, and Slack. There is a new wave of startups trying to change

How to land a Data Scientist job at your dream company — My journey to Airbnb

The process, tips, and some resources Photo by Kalen Emsley on Unsplash The reason that I write this blog I just started my new job at Airbnb as a data scientist a month ago, and I still feel that I’m too lucky to be

Machine Learning Translation and the Google Translate Algorithm

The basic principles of machine translation engines Google Machine Translation Every day we use different technologies without even knowing how exactly they work. In fact, it’s not very easy to understand engines powered by machine learning. The Statsbot team wants

Choosing the Right Metric for Evaluating Machine Learning Models  –  Part 1

n the world of postmodernism, Relativism has been, in its various guises, both one of the most popular and most reviled philosophical doctrines. According to Relativism, there is no universal and objective truth; rather each point of view has its own truth.

Choosing the Right Metric for Evaluating Machine Learning Models — Part 2

In the first blog, we discussed some important metrics used in regression, their pros and cons, and use cases. This part will focus on commonly used metrics in classification, why should we prefer some over others with context.   Definitions Let’s

What is the Difference Between Deep Learning and “Regular” Machine Learning?

That’s an interesting question, and I try to answer this is a very general way. The tl;dr version of this is: Deep learning is essentially a set of techniques that help us to parameterize deep neural network structures – neural

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