Month: September 2018

I bought a plane ticket to the US with no return flight. I’d been studying for a year and I figured it was about time I started putting my skills into practice. My plan was to rock up to the US and get hired. Then Ashlee messaged me on LinkedIn, “Hey I’ve seen your posts … Read more‘I want to learn Artificial Intelligence and Machine Learning. Where can I start?’

Fast RCNN So the next idea from the same authors: Why not create convolution map of input image and then just select the regions from that convolutional map? Do we really need to run so many convnets? What we can do is run just a single convnet and then apply region proposal crops on the … Read moreObject Detection using Deep Learning Approaches: An End to End Theoretical Perspective

Computing the histogram In this section, the histogram was calculated by implementation of python programming code (Python 3.6). For python 3.6, There are a lot of common modules using in image processing such as Pillow, Numpy, OpenCV, etc. but in this program Pillow and Numpy module was used. To import the image from your computer, … Read moreImage Processing Class (EGBE443) #2 -Histogram

Hi all, there is a very quick guide how to configure a system monitoring for one or more servers using a modern stack of technologies like Grafana, Docker and Telegraf with Influxdb. The main goal for this article is to show how to start geting system metrics from your servers quick and easy, without spending … Read moreGet system metrics for 5 min with Docker, Telegraf, Influxdb and Grafana

Before I get into solutions I think it is important to discuss some overarching themes of deep learning. Training Objectives Remember that when we create a neural network, what we are effectively doing is designing an experiment. We have data, a model architecture and a training objective. The data you provide is the models universe … Read moreLazy Neural Networks

Solving package size issues of fbprophet serverless deployment Adi Goldstein / Unsplash I assume you’re reading this post because you’re looking for ways to use the awesome fbprophet (Facebook open source forecasting) library on AWS Lambda and you’re already familiar with the various issues around getting it done. I will be using a python 3.6 … Read moreHow to get fbprophet working on AWS Lambda

We all live in a world where analyzing a massive set of unstructured data is becoming a business need. And the time we spend on the internet is basically the time we spend on social media. Even our daily life is affected by the people around us. And we are tending to change our opinions … Read moreMachine Learning – Particle Swarm Optimization (PSO) and Twitter

Sep 11, 2018 In this blog, we are going to build a neural network(multilayer perceptron) using TensorFlow and successfully train it to recognize digits in the image. Tensorflow is a very popular deep learning framework released by, and this notebook will guide for build a neural network with this library. If you want to understand … Read moreMulti-Layer perceptron using Tensorflow

Sep 9, 2018 We have completed our first basic supervised learning model i.e. Linear Regression model in the last post here. Thus in this post we get started with the most basic unsupervised learning algorithm- K-means Clustering. Let’s get started without further ado! Background: K-means clustering as the name itself suggests, is a clustering algorithm, … Read moreDiving into K-Means…

Reading and processing data for statistical and quantitative analysis in trading Sep 8, 2018 Anyone interested in the statistical analysis of financial markets has the need to process historical data. Historical data is needed in order to backtest or train: Quantitative trading. Statistical trading. Price action replay/walkthrough. Each need comes from different goals. 3 examples on … Read more3 approaches for backtesting historical data