Featured

Number of counties won by each candidate Let’s check how many counties won by each candidate. I will show you two different ways to accomplish this task. The first way is to use the groupby function and count the number of “True” values for each candidate. winner = elections[[‘candidate’,’won’,’state’]]\.groupby([‘candidate’,’won’], as_index=False).count()winner = winner[winner.won == True]winner.rename(columns={‘state’:’won_county’}, inplace=True)winner … Read more Analysis of US Elections 2020 with Pandas

Want to get hired? Work on your technical skills! Want a promotion? Learn institutional knowledge! Domain Knowledge & Institutional Knowledge: When my past company’s CEO encouraged me to work on Declined Transactions as my first project after joining the team, I was disappointed! Right out of academia, I was hoping for a complex project like … Read more Paving the Way to Google!

A part of the Bootstrap Thompson Sampling algorithm (image by author). An uncommon combination allows efficient sequential learning on the edge The multi-armed bandit (MAB) problem is a relatively simple (to describe that is, not to solve) formalization of a sequential learning problem that has many applications. In its canonical form, a gambler faces a … Read more Bandits, WebAssembly, and IoT

A virtual environment is an isolated region where a particular version of Python and its packages are installed enabling the installation of different versions of Python. Each environment has its own files, directories, and paths. Thus a single system can cater to different projects that demand different Python versions. For Python installation and its basics, … Read more Installing Jupyter Notebook for Different Environments in Windows 10

AI for Assistance in Fact-Checking. Now that we have a basic understanding of the problem of fake news, how can we tackle it? Of course, there is always the path of manual fact-checking, such as when news groups fact-check presidential candidates during a debate. And completely opposite of this is the path of automatic fact-checking, … Read more Truth-Seeking in the Post-Truth Era: Tutorial at EMNLP 2020

There appears to be a wide variety of answers to whether you need an advanced degree to get a data science job. Here, I review and explore the educational level, as discussed by Robert Half, Burtch Works, and Indeed. As you begin your data science career, Robert Half and Indeed agree that you should have … Read more Do You Need a Master’s Degree in Data Science?

How to use scatterplots, correlation coefficients, and linear regression effectively Photo by Magda Ehlers from Pexels One of the most common analyses conducted by data scientists is the evaluation of linear relationships between numeric variables. These relationships can be visualized using scatterplots, and this step should be taken regardless of any further analyses that are … Read more Evaluating linear relationships

Let’s take a look at the function in Power BI, you know I love Power Query, so let’s start there. I have a simple table here — a list of units by company. Image by author Basically, I want to rejig this simple data frame into a table that has 2 rows of each company. … Read more Power BI Functions — (List.MaxN, R-slice_max, TOPN)

How to Write Basic GSQL Commands (Note: This is Part 3 of a series. Check out the past blog to load the data into your database!) Now that you have your data loaded, the next big step will be catching them all and extracting relevant information from your graph using queries. This blog will be … Read more PokéGSQL: Create your First GSQL Algorithms with a Pokémon Dataset!

Adding to the Schema and Adding More Data (Note: This is a Part II of a series. Please check out Part I here: https://towardsdatascience.com/using-api-data-with-tigergraph-ef98cc9293d3) In the last blog, we learned how to upsert API data into a graph for a basic schema. Now, we’re going to go deeper, making a more complex schema and adding … Read more Pokémon Lab Part II: Adding More Data

How to add click actions and live updates to the Dash DataTable Photo by Markus Spiske on Unsplash Plotly Dash is an incredibly powerful framework that allows you to create fully-functional data visualization dashboards. Using Dash, you can create a full front-end experience using only Python. The library does a great job of abstracting away … Read more Creating Interactive Data Tables in Plotly Dash

Introduction Why did you choose Data Science? What is your everyday work like? Does Data Science get easier? Where do you see Data Science in 5 years? Will you ever leave Data Science? Summary References Data Science has become an incredibly popular field over the past few years. When I started applying to Masters’s programs … Read more The Top 5 Data Science Questions I Get Asked

It doesn’t replace your job, it only makes it a little easier. Photo by Possessed Photography on Unsplash In the past five years, one trend that has made AI more accessible and acted as the driving force behind several companies is automated machine learning (AutoML). Many companies such as H2O.ai, DataRobot, Google, and SparkCognition have … Read more How to approach AutoML as a data scientist

A practical guide to creating differentially private, synthetic data with Python and TensorFlow In this post, we’ll train a synthetic data model on the popular Netflix Prize dataset, using a mathematical technique called differential privacy to protect the identities of anonymized users in the dataset from being discovered via known privacy attacks such as re-identification … Read more How To Create Differentially Private Synthetic Data

Photo by Amy-Leigh Barnard on Unsplash The era of the monolithic data warehouse/data lake is coming to an end — long live the decentralized data mesh! Oh, do not despair! All those person-years spent cleaning, transferring, and loading data into your centralized systems hasn’t been in vain. With data mesh, you don’t have to start … Read more Data Mesh 2.0

Pruning Neural Networks To obtain fast and accurate inference on edge devices, a model has to be optimized for real-time inference. Fine-tuned state-of-the-art models like VGG16/19, ResNet50 have 138+ million and 23+ million parameters respectively and inference is often expensive on resource-constrained devices. Previously I’ve talked about one model compression technique called “Knowledge Distillation” using … Read more Model Compression via Pruning

Putting It Together By recreating this project, you can improve on these skills: Working with APIs Deploying data apps into production with Streamlit Writing production-level code Scripting A little bit of Plotly geospatial visualization First things first, if you want to run the app on your own machine, you can do so by cloning the … Read more Production-level App With Streamlit and Climacell API in a day

bjecrPhoto by Tamara Gak on Unsplash Google has just announced the launch of MediaPipe Objectron, its mobile technology for real-time detection of 3D objects, enabling the smartphone to recognize the size and orientation of objects. If there one thing that I love in Google’s research is image analysis. The automatic suggestions of Google Photos or … Read more Google Objectron — A giant leap for the 3D object detection

From understanding flow to a quick trick to replace machine learning Photo by Solen Feyissa on Unsplash + Image by Author Sankey charts have become one of the important visualisation techniques in recent time for advanced analytics. It has both characteristics of any awesome visualisation — 1. It can look visually stunning 2. It gives … Read more 4 use-cases for Sankey Charts

Learn how this can accelerate AI solutions to benefit modern medicine. Baby armadillo (image licensed to author) Nowhere is data security, accuracy, and time-to-insight more critical than in the world of healthcare. Rapid deployment of AI is enabling healthcare specialists worldwide to deliver a better service. From AI analysis of MRI scans to aid accurate … Read more Google Cloud Healthcare API

Learn how to output a Pandas DataFrame to Excel with formatting using XlsxWriter Photo by Safar Safarov on Unsplash Being able to extract data from a database and output it to Excel is a crucial skill to have as a Data Analyst. Today we are going to look at using a Python package called XlsxWriter … Read more Python, Pandas & XlsxWriter | by Dean McGrath

Problems in AI Safety — Deliciously Explained Who doesn’t love pizza? Nothing beats the intense smoky flavour and the seasoned crust of a perfect pepperoni pizza ordered in a lazy Friday night. If you too share a passion for pizza and a love for machine learning, the idea of training a robot to make pizza … Read more Problems in AI Safety Explained with a Pizza Robot

Four programming languages, from installation, debugging, tabular data calculation, and more to see which one business people should learn. Image by unsplash.com The most common data in business work is tabular data, such as order records, personnel information, sales contracts, etc., which is called structured data in professional terms. Excel is the most commonly used … Read more What programming language should business people learn?

How to effectively and efficiently use data generators in Keras for Computer Vision applications of Deep Learning I have worked as an academic researcher and am currently working as a research engineer in the Industry. What my experience in both of these roles has taught me so far is that one cannot overemphasize the importance … Read more Image Data Generators in Keras

Keeping track of multiple variables can become a bit of a nightmare during machine learning development. You will often find that data might travel through several functions and they may need to know settings to do their jobs correctly. Photo by Glenn Carstens-Peters on Unsplash Often you find that you need to store some information … Read more Named Tuples: A Little Known Machine Learning Helper

Build a profitable wind energy demand forecasting model for energy traders based on deep learning. Photo by Rabih Shasha on Unsplash Creating a steady supply of energy is always vital as our modern society genuinely depends on this. That is why predictable sources of energy like fossil fuels, or nuclear power, is still favorable. However, … Read more Trading Wind Energy: Wind Energy Forecasting Model based on Deep Learning

What is numeracy in NLP and why it matters? Original image from [Chen, et al. 2020], DeepArt image by DeepArt We humans never really liked math. It’s why we built computers in the first place. One of my first maths teachers once said: “Science & invention, in most cases, is driven by laziness. We don’t … Read more Transformers & Numeracy (Pt 1): Calculators for natural language

A terminal multiplexer is a program that allows users to split a single terminal into one or more virtual sessions. For example, you may want to open Vim in one, and execute a command in another. This can be achieved by opening new terminal tabs but it still doesn’t achieve that level of parallelism. Terminal … Read more Terminal Multiplexers to the Rescue

The input to any LSTM layer is going to be a 3D Tensor, that looks something like this: Image by Author t_0 through t_6 represents your ‘window.’ This could be the length of your sentence, or a window from a time series. v_1 through v_6 represent your ‘features.’ In the case of a univariate time … Read more What’s happening in my LSTM layer?

Duplicates are a recurring problem for any database user. There are several reasons why some duplicates may appear in a data set, and a sanity check is often necessary before any analysis can be conducted properly. This is why I want to share with you some lessons learned from my experience in dealing with duplicates … Read more How To Deal with Duplicate Entries Using SQL

Small, but nonetheless realistic Photo by Cristofer Jeschke on Unsplash GANs are one of the most promising new algorithms in the field of machine learning. With uses ranging from detecting glaucomatous images to reconstructing an image of a person’s face after listening to their voice. I wanted to try GANs out for myself so I … Read more Using GANs to generate realistic images using Keras and the CIFAR10 Dataset

Data Science is great. The idea of analyzing data for decision making has been around for many years, but the popularity of data science has exploded along with the FAANG companies’ growth in recent years. No matter your job title, experience level, or industry, I am confident that you will encounter solutions or products that … Read more 4 ways Data Scientists fool us

Hi there. In this post, I am going to share some interesting stories/applications about graph mining and analytics. Not everyone, even data scientist work with graph-related problems/tools every day. So the first question one might ask: what is a graph? Second: why is graph analytics and algorithms important to know? Third: what are some applications … Read more Introduction to Graph Mining and Analytics

Implementing PPO from scratch with Pytorch In this post, we will train an RL agent to play two control based games: Our agent will be trained using an algorithm called Proximal Policy Optimization. We will implement this approach from scratch using PyTorch and OpenAi gym. This post is based on the following paper: Gym: import … Read more Learning to Play CartPole and LunarLander with Proximal Policy Optimization

As I host these meetings, I share my screen with the developer’s code, and we walk through the work line by line. For our team, it is common that a project may require multiple pull requests in one or more repositories while it is being worked on. Therefore, these discussions allow us to discuss if … Read more 15 Topics to Consider as You Review Code in Data Science