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 neural networks on my own. I’ve just got my first results which I am sharing, but the system looks like a ravel of scripts, binaries, … Read moreAcoustic Noise Cancellation by Machine Learning
After getting scrum.org the PSM I I wanted to capture the relevant content. The complete guido can be downloaded here: scrumguides.org 1. What is Scrum? Scrum is a framework for developing and sustaining complex products. A framework in which complex adaptive problems can be addressed. It is lightweight, simple to understand and yet difficult to … Read moreScrum PSM I
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 much we move towards minima. The small learning rate makes model converge slowly, while the large learning rate makes model diverge. So, the learning rate … Read moreFinding Good Learning Rate and The One Cycle Policy.
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 solve a different business problem. Let’s consider a few examples: Movie/Book/News Recommendations — Suggest new content that increases user engagement. The aim is to introduce users to … Read moreRecommendation Systems — Models and Evaluation
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 in terms of time required to train a convolutional neural network based model for image recognition. As the starting point, I took the blog post … Read moreR vs Python: Image Classification with Keras
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, check this post for getting a clear idea about Machine Learning and it’s basics. What is the logic behind simple linear regression model? As the … Read moreLinear Regression Model
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 on ESP using Jupyter, we learned how to install and run MicroPython on an ESP device. Using Jupyter Notebook as our development environment, we also … Read moreIoT Made Easy: ESP-MicroPython-MQTT-ThingSpeak
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 then mounting Drive onto the Colab environment. But a lot of open sourced large datasets that are available for research purposes, are hosted on Github/Gitlab. … Read moreFrom Git to Colab, via SSH
Since R is mostly a functional language and data science work lends itself to be expressed in a functional form you can come by just fine without learning about object-oriented programming. Personally, I mostly follow a functional programming style (although often not a pure one, i.e. w/o side-effects, because of limited RAM). Expressing mathematical concepts in … Read moreObject Oriented Programming in Data Science with R
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 to achieve economic effectiveness, but around 75% of them failed or created problems that were serious enough to threaten organization’s survival (1). It has been … Read moreDevOps: To do or not to do?