## Math Behind Reinforcement Learning, the Easy Way

Aug 2, 2018 Photo by JESHOOTS.COM on Unsplash Look at this equation: Value function of Reinforcement Learning If it does not intimidate you, then you are a mathematical savvy and there … Read more

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## Cooking with Machine Learning: Dimension Reduction

Recently I came across this cooking recipes data set in Kaggle, and it inspired me to combine 2 of my main interests in life. Food and machine learning. What makes … Read more

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## An In-depth Review of Andrew Ng’s deeplearning.ai Speciliazation

So you’ve seen the recent news about how artificial intelligence (AI) is changing everything. However, the idea of AI has been around for a long time. Machines that think and … Read more

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## An Advanced Example of Tensorflow Estimators Part (1/3)

Estimators were introduced in version 1.3 of the Tensorflow API, and are used to abstract and simplify training, evaluation and prediction. If you haven’t worked with Estimators before I suggest … Read more

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## Hypothesis Analysis Explained

Jul 19, 2018 Hypothesis analysis is a widely known concept and is used extensively by researchers, statisticians and quantitative analysts. It allows them to follow a set of formal steps … Read more

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## PySpark ML and XGBoost full integration tested on the Kaggle Titanic dataset

Jul 8, 2018 In this tutorial we will discuss about integrating PySpark and XGBoost using a standard machine learing pipeline. We will use data from the Titanic: Machine learning from … Read more

## Acoustic Noise Cancellation by Machine Learning

DIY Noise-Cancellation System prototype made with TensorFlow. Jun 25, 2018 Image by TheDigitalArtist on Pixabay In this post I describe how I built an active noise cancellation system by means of … Read more

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## Finding Good Learning Rate and The One Cycle Policy.

Introduction Learning rate might be the most important hyper parameter in deep learning, as learning rate decides how much gradient to be back propagated. This in turn decides by how … Read more

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## Recommendation Systems — Models and Evaluation

I’ve been involved in building several different types of recommendation systems, and one thing I’ve noticed is that each use case is different from the next, as each aims to … Read more

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## R vs Python: Image Classification with Keras

Many data professionals are strict on the language to be used for ANN models limiting their dev. environment exclusively to Python. I decided to test performance of Python vs. R … Read more

## Linear Regression Model

Jun 14, 2018 This post is about implementing simple linear regression model for ML beginners in step by step way with detailed explanation. If you are new to machine learning, … Read more

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Using MQTT protocol, we will get captured data from sensors, logging them to an IoT service, ThingSpeak.com and to a mobile App, Thingsview. 1. Introduction In my previous article, MicroPython … Read more

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## From Git to Colab, via SSH

When you are using Google’s Colaboratory (Colab) for running your Deep Learning models the most obvious way to access the large datasets is by storing them on Google Drive and … Read more

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## DevOps: To do or not to do?

Over the past few decades, four key change initiatives have been taking place in the organizations: strategic planning, re-engineering, total quality management and downsizing. The aim of these initiatives was … Read more

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## The Mathematics of Decision Trees, Random Forest and Feature Importance in Scikit-learn and Spark

This post attempts to consolidate information on tree algorithms and their implementations in Scikit-learn and Spark. In particular, it was written to provide clarification on how feature importance is calculated. … Read more

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## Implementing QANet (Question Answering Network) with CNNs and self attentions

Apr 15, 2018 In this post, we will tackle one of the most challenging yet interesting problems in Natural Language Processing, aka Question Answering. We will implement Google’s QANet in … Read more

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## What I wish I’d done differently as a data science manager

On centralizing siloed data Apr 12, 2018 I still get nostalgic looking at the very first Pebbles. (Photo courtesy of Pebble’s first Kickstarter) In 2014, I joined Pebble, the smartwatch maker … Read more

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## Machine Learning for People Who Don’t Care About Machine Learning

Greg Lamp, previous co-founder of the data science startup Yhat, and current co-founder & CTO of Waldo shares his thoughts on Machine Learning for those of us who just don’t … Read more

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## Hierarchical Clustering on Categorical Data in R

Dissimilarity MatrixArguably, this is the backbone of your clustering. Dissimilarity matrix is a mathematical expression of how different, or distant, the points in a data set are from each other, … Read more

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## Which Leading Artificial Intelligence Course Should You Take and What Should You Do After?

4. Course Content The content of each course is world-class. I’ve frequently stated in my videos these are the best courses I’ve ever taken. The DLND is broken into six … Read more

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## Automatic GPUs

A reproducible R / Python approach to getting up and running quickly on GCloud with GPUs in Tensorflow “A high view of a sea of clouds covering a mountain valley … Read more

## Crossing Your Data Science Chasm

An analytics roadmap for growth Scenario — You’re an up-and-coming ecommerce/SaaS startup. You’ve got your site up, you have A/B tested your message, and you’ve got your SEO, and social … Read more

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## Quick implementation of Yolo V2 with Keras!

Feb 22, 2018 I do not hold ownership to any of the above pictures. These are merely used for educational purposes to describe the concepts. Real time multiple object localization … Read more

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## Ordinal Logistic Regression

An overview and implementation in R Feb 19, 2018 Fig 1: Performance of an individual — Poor, Fair, Excellent Can you guess what is the common link in the variables mentioned below: Job … Read more

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## Writing Custom Keras Generators

The idea behind using a Keras generator is to get batches of input and corresponding output on the fly during training process, e.g. reading in 100 images, getting corresponding 100 … Read more

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## Tips for Using Data to Solve Company Issues that You Can Master Today

It’s not enough to do data analysis (Credit rawpixel: Unsplash) Stop management from ignoring your analysis Feb 3, 2018 To a data analyst, there is nothing more exciting than the data … Read more

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## On the importance of DSLs in ML and AI

4) Under the hood: expressing computations TensorFlow could be considered a programming system and runtime, not just a “library” in the traditional sense: TensorFlow’s graph even supports constructs like variable … Read more

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Jan 13, 2018 The computing world has seen increasing attention on microservices software architecture in order to enhance software scalability and efficiency. Microservices brings many benefits for tech organizations. However, … Read more

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## AWS EC2 for Beginners

Discover why you should use Amazon Web Services Elastic Compute Cloud (EC2) and how you can set up a basic data science environment on a Windows Virtual Machine (Windows Server). … Read more

## Reinforcement Learning Series — 01 (Key Concepts)

Reinforcement Learning (RL) is one of the most happening field of Machine Learning (ML) and Artificial Intelligence (AI).Though RL existed for many decades, only recently the giant has awaken after … Read more

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## ToneNet : A Musical Style Transfer

Nov 27, 2017 By: Team Vesta, University of Southern California. CSCI:599 Deep Learning and Its Applications Suraj Jayakumar (sjayakum@usc.edu), Rakesh Ramesh (rakeshr@usc.edu), Pradeep Thalasta (thalasta@usc.edu) Introduction: The recent success of … Read more

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## Finding Magic: The Gathering archetypes with Latent Dirichlet Allocation

Combining card games and topic modeling Nov 27, 2017 This article sparked an interesting discussion on reddit and was featured by Wizards of the Coast. One of the coolest projects I’ve … Read more

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## Binary Logistic Regression

An overview and implementation in R Oct 31, 2017 Customer satisfaction for a product — Satisfied vs Dissatisfied (Source: pixabay.com) Have you ever come across a situation where you want to predict a … Read more

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## Hard Problems in Data Science: Causality, Sequential Learning and Complex Dynamic Theories

Oct 20, 2017 In the second of four informal discussion sessions, Professor Maurits Kaptein from Tilburg University discussed the methodological challenges of data science. ‘’Before discussing the biggest challenges we … Read more

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## CycleGANS and Pix2Pix

Aug 15, 2017 Credits: Presenting abridged version of these blogs to explain the idea and concepts behind pix2pix and cycleGANs. Christopher Hesse blog: Olga Liakhovich blog: Pix2Pix: paper: https://phillipi.github.io/pix2pix/ pix2pix … Read more

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## How I’m Learning Deep Learning in 2017 — Part 3

I’ve said yes to far too many hidden units Part of the How I’m Learning Deep Learning Series: Part I: A new beginning.Part II: Learning Python on the fly.Part III: … Read more

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## Attempting to Visualize a Convolutional Neural Network in Realtime

While replicating the End-to-End Deep Learning approach for Self- Driving Cars, I was frustrated by the lack of visibility into what the network is seeing. I built a tool to … Read more

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## Perceptron : Where It All Started

Implementing the Perceptron Perceptron is one the most elegant yet easy to implement learning algorithms. Though most packages/libraries provide implementation for this algorithm, let us try our hand on it … Read more

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## Visualising high-dimensional datasets using PCA and t-SNE in Python

Oct 29, 2016 Update: April 29, 2019. Updated some of the code to not use ggplot but instead use seaborn and matplotlib. I also added an example for a 3d-plot. … Read more

## A Concise History of Neural Networks

Aug 13, 2016 “From the barren landscapes inside our personal devices come furtive anthems hummed by those digital servants who will one day be our overlords” A.I. winter The idea … Read more

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## Shell Basics every Data Scientist should know

This will make your life easy. Thank me later Oct 8, 2015 Photo by Markus Spiske on Unsplash Shell Commands are powerful. And life would be like hell without shell is how … Read more

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