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A convolutional auto encoder based approach for semi-supervised anomaly detection in images. In this article, I’ll be discussing a paper [1] that proposes an AutoEncoder based approach for the task of semi-supervised anomaly detection. If you want to look at the GitHub repository link, results and conclusion directly, please scroll to the bottom of the … Read more Semi-supervised Anomaly Detection using Auto Encoders

I was at an airport recently — a statement I didn’t think I would be able to make for another year or so. And I don’t know about you guys but I feel like I have been cursed by the airport gods because for some reason, I can never get past baggage check-in without overweight … Read more Explain by Example: Deep Learning (NN)

References: [1] N. Even-Chen, D.G. Muratore, S.D. Stavisky, and et al. Power-saving design opportunities for wireless intracortical brain computer interfaces. (2020) Nat Biomed Eng. [2] X. Li, T. Adali, and M. Anderson. Noncircular principal component analysis and its application to model selection (2011). IEEE Transactions on Signal Processing, 59(10):4516–4528. [3] David A. Markowitz, Yan T. … Read more Non-circular PCA and Neural Decoder

This article is part 2 of a series of articles that aim to highlight the aesthetics that can be found in the computational world and data universes. It is as Walframe puts it an “abstract voyages in the computational world”. Patterns in nature and the computational world In this article, we will discuss patterns that … Read more Aesthetics Within the Computation World- Part 2: Turing Patterns

What is it like to be a data scientist? In October 2012, a Harvard Business Review article described data scientist as the sexiest job of the 21st century. This article is not the reason why data science is so popular now but I’m pretty sure it motivated some people to become a data scientist. Before … Read more The Dark Side of the Sexiest Job of the 21st Century

If there’s one thing I know for sure, EVERYONE loves data visualizations, even if they don’t necessarily like data. Think about how popular Spotify’s 2019 Wrapped was to give an example. Wasting no time, I wanted to share with you the ten most fascinating data visualizations that I saw this year and why they’re so … Read more My Top 10 Most Fascinating Data Visualizations From 2020

Image by Author After having spent many months and possibly millions of dollars collecting data through a survey or census, researchers are grappling with the problem of understanding and cleaning the data. Representing them as a graph in a graph database is a novel approach to achieve this. Here I’ll show the benefits of having … Read more Why You Should Store Your Survey Data in a Graph Database

What do gunslingers like Wyatt Earp have in common with Data Analytics and Science you might ask yourself — it’s about small probabilities (to stay alive as a gunman) and how it can result in selection bias. Photo by Steve on Pexels What on Earth is the Wyatt Earp Effect? The Wyatt-Earp effect or the … Read more Wyatt Earp Effect and its Consequences for Data Analytics and Science

What was the problem? Well, I trusted my sister more than my parents to give me the right answer. I assigned more weight to my sister’s explanation than my parents’ answer. Next time, I’ll know to listen more to my parents and less to my sister. This process of adjusting weights is called backpropagation. When … Read more Learn How Neural Networks Learn

image source — https://unsplash.com/@bacila_vlad This is my first Medium article! (Yay!!!) The project is based on my capstone project for my master’s in data science. I had a lot of fun and I learned so much. I would love to here your feedback on this project if you have some free time. You can find … Read more Harnessing the power of transfer learning for medical image classification

Install QGIS QGIS can be painlessly installed from their website here. At the time of writing I’m using version 3.16.1 so expect things to look slightly different in later versions. Ground Yourself! When you first open QGIS you’ll be faced with a blindingly white background with tons of tiny buttons on the top and sides. … Read more A Beginners Guide to Feature Engineering with QGIS

Binned Average Monthly Hours (Left: Fixed width cut, Right: quartile cut) Occasionally there are many null values which might invoke error during one hot encoding or machine learning operations. Therefore, we might want to remove or impute the null values in the specified features. There are many strategies to impute values such as median, mean, … Read more Simple Yet Effective Data Preprocessing Toolbox

Usually, this is something we don’t do. You can sometimes upsample test data anyway just to see if your model works well on minority classes as well. What’s most important to keep in mind is that you don’t want to upsample data and only then do a data split into train and test set. This … Read more Machine Learning: Target Feature Label Imbalance Problem and Solutions

Source: Photo by Loic Leray on Unsplash Thirty years from now, will we look back at 2020 as the year when AI discriminated against minority groups, disinformation propagated by special interest groups and aided by AI-based personalization caused political instability, deep fakes and other AI-supported security infringements basically rendered AI untrustworthy and propelled us into … Read more Five Views of AI Risk

How can we used unsupervised learning to describe COVID-19 trends in the United States Analytics has become a part of everyone’s daily routine as a result of the pandemic. Every day we look at curves of new cases, positivity rates, and a range of other metrics that give us insight into our current situation. One … Read more Clustering U.S counties by their COVID-19 curves

Generate quotes at will Good quotes help make us stronger. What is truly inspiring about quotes is not their tone or contentedness but how those who share them reflect life experiences that really serve others. I didn’t write the above quote about quotes (Quote-ception; bad pun?), but an AI model I trained did. And it … Read more How to Train and Deploy Custom AI-Generated Quotes using GPT2, FastAPI, and ReactJS

Why probabilistic thinking can be an extraordinarily powerful and practical tool to approach the unknown and uncontrollable Photo by Loic Leray on Unsplash In a video published in November 2020, physician and philosopher of science Etienne Klein called for engineers to express their opinions and participate in a public debate. As a result, I decided … Read more The importance of probabilistic thinking when faced with uncertainty

Using a bread vs. cake classifier to deconstruct random forests Photo by Rod Long on Unsplash If only machine learning could be as delicious as it is oftentimes perplexing. While learning data science concepts, I’ve found that it’s a good idea to approach it the same way as learning baking: start simple, grab the basic … Read more The Great British Baking Show: Random Forests Edition

The NotionAPI Gem is available for installation here, and the GitHub repository is here. To get started, all you need is to retrieve your token_v2 credentials (open a Notion session in the browser, navigate to cookies, and look for the token_v2 key). After that, you can begin a session with the following code: require “notion_api”@client … Read more Introducing the Notion API Ruby Gem

Now it’s time to address all the questions based on the concept of the random variable presented above. Question1: “What is the probability he can join the team with a crew size of 4, P(X=4)?” To do so, we can calculate the proportion of times for X = 4 to occur. Such proportion of time … Read more Introducing Discrete Random Variable and Expected Value using NASA Data

Location Data Using BeautifulSoup, a Python library used for pulling data out of HTML we parse the Wikipedia page to get the list of neighborhoods and districts in Los Angeles. Using Google’s Geocoding API, we collect the location data such as Latitudes and Longitudes of each neighborhood and store them into a pandas dataframe. DataFrame … Read more Los Angeles Neighborhood Analysis

Learn all the statistics you need for data science for free Photo by Daniel Schludi on Unsplash Statistics is a fundamental skill that data scientists use every day. It is the branch of mathematics that allows us to collect, describe, interpret, visualise, and make inferences about data. Data scientists will use it for data analysis, … Read more 5 Free Books to Learn Statistics for Data Science

Manage licensing risks of Open Source Data Science projects The best AI/ML software today from model development (scikit-learn, TensorFlow, PyTorch) to deployment (Kubeflow, Spark) is Open Source. The below snapshot should give you an idea of the pervasiveness of Open Source Software (OSS) in the Enterprise. OSS enterprise adoption trends While OSS started as a … Read more Open Source Licensing primer for Enterprise AI/ML

MPNet is a hybrid of Masked Language Modeling(MLM) and auto-regressive Permuted Language Modeling(PLM) adopting the strengths and avoiding their limitations from each of its constituents. Masked language modeling, as in BERT-style models, mask out ~15% of the data and try to predict those masked tokens. As the dependency between the masked tokens is not modeled … Read more NeurIPS 2020 Papers: A Deep Learning Engineer’s Takeaway

Programming The path from the very beginning to the further high-quality programming practices. Photo by Jefferson Santos on Unsplash Do you want to learn to program like an engineer? From the ground up by focusing on performance and high standards? If you want to learn programming in a month probably this article is not for … Read more Programming Path For Those Failing to Learn Programming

To implement the ADF test in python, we will be using the statsmodel implementation. Statsmodels is a Python module that provides functions and classes for the estimation of many statistical models. The function to perform ADF is called adfuller. First, import the required dependencies. Import the statsmodel module and the adfuller class from the tsa.statstools … Read more How to Check if our Time Series is Stationary or Not and Why?

Torch your Data Science world alight with these Tensor related functions “How many Marks did you get in your data science class?” “10 out of tensor” | Photo by Ales Nesetril on Unsplash PyTorch is one of the most sought after skill when it comes to recruitment for data scientists. For those who don’t know, … Read more 5 Powerful PyTorch Functions That Every Beginner Should Know

The difference, which is the key hallmark of the Q Learning algorithm, is how it updates its estimates. The equation used to make the update in the fourth step is based on the Bellman equation, but if you examine it carefully it uses a slight variation of the formula we had studied earlier. Let’s zoom … Read more Reinforcement Learning Explained Visually (Part 4): Q Learning, step-by-step

Analyzing the last ten NBA drafts to determine who drafts well and who doesn’t Photo by Chensiyuan on Wikimedia Commons Drafting is one of the most crucial elements of a successful long-term franchise. Fueled by a series of great draft picks, the San Antonio Spurs went on to make the playoffs for a record-tying 22 … Read more Which NBA teams are best at drafting?

Deep learning papers, blog posts, Github repos, etc. that I liked this week Photo by Sebastian Pena Lambarri on Unsplash This is the second edition of my weekly update on deep learning. Every Thursday, I’ll release a new batch of research papers, blog posts, Github repos, etc. that I liked over the past week. Links … Read more Keeping Up with Deep Learning — 26 Nov 2020

About my hustle before cracking interviews. It took me one year to go from a noob programmer to someone decent enough to crack coding interviews for getting internships and gaining experience. I still have a long way to go, but the first step to being a good programmer is working in the real world and … Read more The One year plan for competitive coding.

Lastly, if these past two years have taught me nothing else, they taught me to take a step back from coding and walk away. When working on an analysis or developing some software or tool, it can be common to keep chugging away on the project. You can often find yourself hours deep into something … Read more 5 Technical Behaviors I’ve Learned from 2 Years of Data Science and Engineering

A quick literature review and example MNIST fits I’ve wanted to learn more about neural nets and in particular TensorFlow for a while now. I recently had a bit more time to dedicate to it, so began to write about what I had learned and some of the basic examples I had ran through. Even … Read more Playing with TensorFlow

HR interview The first step after your resume passes the initial requirements screen is a call with HR. This call is typically with the recruiter for the position to get a sense of your job experience, provide you details about the position, gauge your interest, and ask about your salary expectations. There are many guides … Read more What to Expect in a Data Analyst Interview

While it is important to measure and track the actual CLTV from the existing customer base, a company also need to be able to estimate the CLTV for both existing and prospect customers over the extended period. There are a few things you will need to consider while predicting the CLTV: Forecasting Demand When it … Read more Understanding and Forecasting Customer Lifetime Value (CLTV)

Picture by Carlos Muza on Unsplash. A/B testing is a tool that allows checking whether certain causal relationship holds. For example, a data scientist working for an e-commerce platform might want to increase the revenue by improving the design of the website. If we assume that the revenue is a function of the proportion of … Read more A gentle introduction to the mathematics behind A/B testing

Read Time: 33 mins Target Audience: Machine Learning Engineers (Mobile focused) Review This article is a transcription of a podcast, for readers who prefer to listen as opposed to read, click here to view the video version. This article details the conversation held between Jeremie Harris and Matthew Stewart on subject matters concerning machine learning … Read more Interesting AI/ML Articles On Medium This Week (Nov 28)

A short overview of both tools and how to integrate them in each other — explained with three typical use cases. Overview Alteryx is known as a platform that combines analysis, data science and process automation. Integration with BigQuery — Google’s powerful Data Warehouse technology — can be realized very easily and used for many … Read more How to combine Alteryx and BigQuery

Sometimes Linearity is not sufficient Nick Fewings via Unsplash Logistic Regression is a common method used for fitting a binary or categorical response variable. But did you know that if you are not careful, logistic regression can miss out on important features? In this in depth article, we will use the South African Heart Disease … Read more From Logistic Regression to Basis Expansions and Splines

Can we even decide which forecasting model is the best? All models are wrong, but some are useful — George Box Predictions from various epidemic models are driving crucial global policies. But their estimates are all over the place — So which one do we trust? For this, we need to understand the various sources … Read more The Trouble with Predictions

Exploring coffee similarities using cupping grades and flavors After trying a variety of coffees from around the world, I have often wondered if coffee grades or flavors could tell me which coffees were similar to each other and which were different. I am particularly interested if such comparisons could be used to help determine the … Read more Comparing Coffee using Pattern Recognition

They both use physics, it should be easy Word adjacency graph of common adjectives and nouns in “David Copperfield” (image by the author). Displaying a graph or a network in a way that is not a complete mess can be hard. You want the most connected nodes to be close to each other, and to … Read more 3D force-directed graphs with Unity