Python Input, Output and Import

In this tutorial let us understand the Input and Output built-in-functions used in python, also we will learn how to import libraries and use them in our programs. Image Credits: Data Flair Before getting started let us understand what are built-in-functions? Any function that is provided as part of a high-level language and can be … Read morePython Input, Output and Import

“OK Boomer” escalated quickly — a reddit+BigQuery report

You can now play with the interactive dashboard, to find all sorts of patterns within these comments: Play with the interactive report, or load it full size. I used two different sources of data: To extract all of the historical reddit comments, I used this query: CREATE TABLE `reddit_extracts.201906_all_okboomer`PARTITION BY fake_dateCLUSTER BY subreddit, tsASSELECT TIMESTAMP_SECONDS(created_utc) … Read more“OK Boomer” escalated quickly — a reddit+BigQuery report

And The Star of the Show is — PYTHON

The overall contributions to the open-source projects are seen from all the continents and Asia is on the top with most of its contributions coming from China. The below graph shows us contributions from different continents. The top 50 packages in each language ecosystem have a massive amount of dependent projects. The top npm packages … Read moreAnd The Star of the Show is — PYTHON

How To Compute Satellite Image Statistics And use It In Pandas

The Sentinel 2 image of the area( only Band 3) is shown below. Let us also read the buildings table which we will use to store the statistical summaries derived from the satellite image. Please know that you can use other polygons, like districts, rectangular grids instead of the building polygons for this example. We … Read moreHow To Compute Satellite Image Statistics And use It In Pandas

Explicit AUC maximization

How to explicitly optimize for maximum area under ROC Photo by André Sanano on Unsplash I was getting started on “IEEE-CIS Fraud Detection” Kaggle competition, and something caught my eye: The fact that the results are evaluated based on AUC makes sense for fraud detection tasks for several reasons: The data sets are often unbalanced, … Read moreExplicit AUC maximization

Data-Driven Marketing Attribution

Conversion ratio example Let’s walk through an example using channel conversion ratios. Say that your company converted 100 opportunities at the end of a fiscal quarter. During that period, the marketing department advertised to the associated accounts using three channels: N = {Facebook, Google, LinkedIn} All 100 accounts were touched by one or more of … Read moreData-Driven Marketing Attribution

Interpretability: Cracking open the black box — Part I

How can we bring explainability to the black boxes we use in ML? Interpretability is the degree to which a human can understand the cause of a decision — Miller, Tim[1] Explainable AI (XAI) is a sub-field of AI which has been gaining ground in the recent past. And as I machine learning practitioner dealing … Read moreInterpretability: Cracking open the black box — Part I

Ten Elements of Machine Learning Interviews

A list of online resources that are really helpful. As a PhD student, I have a fairly good understanding of ML algorithms but still found machine learning interviews challenging. The challenge comes from the fact that there is so much more than model fitting in a ML project. Most textbooks cover rather technical details that … Read moreTen Elements of Machine Learning Interviews

What is Deep Learning and How does it work?

During gradient descent, we use the gradient of a loss function (or in other words the derivative of the loss function) to improve the weights of a neural network. To understand the basic concept of the gradient descent process, let us consider a very basic example of a neural network consisting of only one input … Read moreWhat is Deep Learning and How does it work?

Daily Data Science 101 — How rich you need to be in order to beat Casino?

Just graduate from high school, your parents may give you the first tuition. However, it seems like the university does not want to charge you right after you enter the school. What would you do? Casino Actually, Don’t do that and here are the reasons why you should, from a data scientist. You may hear … Read moreDaily Data Science 101 — How rich you need to be in order to beat Casino?

Google vision API for image analysis with python

Google Vision API detects objects, faces, printed and handwritten text from images using pre-trained machine learning models. You can upload each image to the tool and get its contents. But, if you have a large set of images on your local desktop then using python to send requests to the API is much feasible. This … Read moreGoogle vision API for image analysis with python

Machine Learning in Cognitive Science and application in Cyber Security

The world is growing at a faster pace. The increasing reliance on cyber infrastructure by governments, industries, and economies makes them more vulnerable and increases the chances for cyber attacks. Machine Learning in Cognitive Science and application in Cyber Security In their most disruptive form, cyber-attacks target the enterprise, military, government, or other infrastructural resources … Read moreMachine Learning in Cognitive Science and application in Cyber Security

Build a React + Flask App that Suggests Novel Novels with a Python Graph

Project Summary: Build a Graph database of Users and the Books they read Develop a Flask App that serves up rare, interesting Books to Users based on their submitted favorites Implement a React App that integrates with Flask + our Graph to showcase to users their next favorite book There are a lot of great … Read moreBuild a React + Flask App that Suggests Novel Novels with a Python Graph

How to Use Pretrained Models in Keras

Image by Wendy This guide will be useful if you are a bit familiar with pretained models but want to know how to use them in Keras. Keras contains 10 pretrained models for image classification. These models are trained on Imagenet data. In a simplified way, Image classification model looks like following. Pretrained Model The … Read moreHow to Use Pretrained Models in Keras

In Praise Of The Career Changer

It’s Often Hard And Under-appreciated But Here’s To Making Sure That Your Efforts and Struggles Don’t Go Unnoticed Career changers are frequently under-appreciated. I think it’s because our society tends to frown upon discontent or ennui. If someone is struggling to stay engaged at their job, society’s go-to response is, “Suck it up and be … Read moreIn Praise Of The Career Changer

Journey to the world championship — Microsoft Imagine Cup 2019

Consider a situation where Jack and his 7-year-old daughter Ellen are traveling to China. After a tiring day, they enter a supermart to buy something only to realize that all products have information written in Mandarin. Ellen had already been hospitalized twice because of her allergy to nuts. Spot accepts Ellen’s health profile and allows … Read moreJourney to the world championship — Microsoft Imagine Cup 2019

Linear Algebra and Probability Theory Review for ML

Probability theory is our way of dealing with uncertainty in the world, It’s the mathematical framework that estimates the probability of an event happening with respect to other possible events. Probability is at the very deep level of many machine learning algorithms. Let’s discuss the most famous experience that explains probability theory. Tossing a fair … Read moreLinear Algebra and Probability Theory Review for ML

3 Signs that AI Research is About to Hit Trouble

Despite some impressive achievements, and breathless predictions about the future, it feels like something might be wrong in the world of AI. No, this isn’t yet another post about “our new silicone masters”. In fact, what keeps me awake at night is something like the opposite: If you believe the function of AI research is … Read more3 Signs that AI Research is About to Hit Trouble

Where do you fall on the data science distribution?

Ever feel like you destroyed a job interview and then ended up not getting the job. Or how about completely bombing a technical screen and still passing onto the next round? You’re not alone, hiring standards are confusing at best but it still begs the question: how do you know how well you’re performing in … Read moreWhere do you fall on the data science distribution?

America’s Clustered Consensus

Whatever happened to “majority rule”? A continual source of democratic frustration today is that public opinion does not seem to directly translate into public policy. For example, a large majority of Americans want to see campaign finance reform, background checks for gun ownership, and reductions in fossil fuel consumption. Yet, while overwhelming public support has … Read moreAmerica’s Clustered Consensus

What I Discovered About Opportunity Zones From Analyzing Half a Million Data Points

There has been a lot of buzz about Opportunity Zones recently and understandably so; it is the newest federal effort to create long-term investments in low-income urban and rural census tract areas. Once designated as a qualified Opportunity Zone, these places are able to receive investments through Opportunity Funds, which are created specifically to invest … Read moreWhat I Discovered About Opportunity Zones From Analyzing Half a Million Data Points

Data Science of Evictions

Dramatic visualization of 2016 eviction filings by state at the National Building Museum From April 2018 through May 2019, a gallery wing of the D.C. National Building Museum was transformed into a labyrinth of forbidding plywood structures, towering piles of shrinkwrapped home furnishings, and striking visual displays. The exhibition showcased the statistics and stories revealed … Read moreData Science of Evictions

H2O Driverless AI: Data Science without Coding

AI that does AI — Develop your first model today. Anyone can be a Data Science. No Coding Required. Photo by Frank Albrecht on Unsplash In today’s world, being a Data Scientist is not limited to those without technical knowledge. While it is recommended and sometimes important to know a little bit of code, you … Read moreH2O Driverless AI: Data Science without Coding

How to deliver concrete business value with your data science team?

Rapid development in the space of machine learning and deep learning has resulted in advanced algorithms. These advanced algorithms are capable of transforming organizations to derive multi-fold business value. Organizations have started investing in data science teams to lead the digital transformation journey to be at the top of their game. Image by Gerd Altmann … Read moreHow to deliver concrete business value with your data science team?

The AI Race continues to heat up at the GPU Technology Conference 2019

Here’s a startup founder’s perspective of Nvidia’s GPU Technology Conference. Whether you’re wondering how 5G will create new opportunities or why Ghost Restaurants require AI, it’s a good idea to stay up-to-date in this fast moving field. Definition of AI: Capability of an engineered system to acquire, process, and apply knowledge and skills I like … Read moreThe AI Race continues to heat up at the GPU Technology Conference 2019

Build and Compare 3 Models — NLP Sentiment Prediction

Finally, I used the Random Forest algorithm, which is just a combination of a number of decision trees. In my example, I chose to use 300 trees, but I could change that number depending on the kind of accuracy I want from the model. X~i || Fitting Random Forest Classification to the Training set classifier … Read moreBuild and Compare 3 Models — NLP Sentiment Prediction

Why I Donate All of My Book’s Proceeds to Girls Who Code

Grace Hopper, Ph.D. (Vassar Archives) Doing a small part to help close a gender gap Few, if any, of my classmates shared my fascination with the Mark I Computer that was on display in our university’s Science Center. It is hard to blame them. Towering at 8 feet and filled with rotary switches, crystal diodes, … Read moreWhy I Donate All of My Book’s Proceeds to Girls Who Code

Fake Face Generator Using DCGAN Model

The implementation part is broken down into a series of tasks from loading data to defining and training adversarial networks. At the end of this section, you’ll be able to visualize the results of your trained Generator to see how it performs; your generated samples should look fairly like realistic faces with small amounts of … Read moreFake Face Generator Using DCGAN Model

Deploy A Text Generating API With Hugging Face’s DistilGPT-2

For the better part of a year, OpenAI’s GPT-2 has been one of the hottest topics in machine learning — and for good reason. The text generating model, which initially was dubbed “too dangerous” to be released in full, is capable of producing uncanny outputs. If you haven’t seen any examples, I recommend looking at … Read moreDeploy A Text Generating API With Hugging Face’s DistilGPT-2

From Dev to Prod – All you need to know to get your Flask application running on AWS

Getting the right configurations, making sure it is secured, ensuring resource access through endpoints and having a pretty rendering, … all of them made easy thanks to AWS! As a machine-learning engineer, I never really faced the issue of putting my algorithms out there myself. Well, that was until recently, when I decided to start … Read moreFrom Dev to Prod – All you need to know to get your Flask application running on AWS

Building a machine learning classifier model for diabetes

Based on medical diagnostic measurements Python codes are available: https://github.com/JNYH/diabetes_classifier The Pima Indians of Arizona and Mexico have the highest reported prevalence of diabetes of any population in the world. A small study has been conducted to analyse their medical records to assess if it is possible to predict the onset of diabetes based on … Read moreBuilding a machine learning classifier model for diabetes

AiPM

So what? The cost scales exponentially and unpredictably. The example we shared is just to manage one model, for one business line, and for one model cycle (a different issue may happen in the future). Now, imagine scaling this process to hundreds of models for multiple business units and functions. The bottom line: companies cannot … Read moreAiPM

How Spotify Recommends Your New Favorite Artist

A story of data, taste, and a very effective recommender system. Just a short few days ago, I was discussing the impact of recommender systems with some students on a course I’m teaching. Netflix, Amazon, Facebook, and many other online services, use our data to suggest other products we might like. Is this helpful, or … Read moreHow Spotify Recommends Your New Favorite Artist

What do campaign contributions tell us about the federal election?

With Canada’s 43rd Federal Election not too far in the rearview mirror, we at ThinkData Works were curious as to what we can learn about our most recent election by stepping back from the punditry and analyzing some data. After all, using government data is a great way to understand how our government works. There … Read moreWhat do campaign contributions tell us about the federal election?

Quickly Build and Deploy an Application with Streamlit

With the launch of Streamlit, developing a dashboard for your machine learning solution has been made incredibly easy. Streamlit is an open source app framework specifically designed for ML engineers working with Python. It allows you to create a stunning looking application with only a few lines of code. I want to take this opportunity … Read moreQuickly Build and Deploy an Application with Streamlit

The hardest question you’ve been asked in a data science interview

What’s the most difficult question you ever encountered in a data science interview? I’ll share mine: “How many years of experience do you have in language X?” This is really hard to answer: Do I count the years I used it in academia? Do I count the years I used it in my hobby projects? … Read moreThe hardest question you’ve been asked in a data science interview

Take your Machine Learning Models to Production with these 5 simple steps

I have created this impressive ML model, it gives 90% accuracy, but it takes around 10 seconds to fetch a prediction. Is that acceptable? For some use-cases maybe, but really no. In the past, there have been many Kaggle competitions whose winners ended up creating monster ensembles to take the top spots on the leaderboard. … Read moreTake your Machine Learning Models to Production with these 5 simple steps

Full Stack Development Tutorial: Serverless REST API running on AWS Lambda

Serverless computing is a cloud-computing execution model in which the cloud provider runs the server, and dynamically manages the allocation of machine resources. Pricing is based on the actual amount of resources consumed by an application, rather than on pre-purchased units of capacity. — Wikipedia Photo by Anthony Cantin on Unsplash (This is the second … Read moreFull Stack Development Tutorial: Serverless REST API running on AWS Lambda

How I Use AI Across One of My Favorite Hobbies — Photography

Neural Networks for labeling, compression, effects and more! You can read the article and follow along with the code in the repo: Poseyy/AI-Photography You can’t perform that action at this time. You signed in with another tab or window. You signed out in another tab or… github.com An obvious application of AI to photography is … Read moreHow I Use AI Across One of My Favorite Hobbies — Photography

Online Marketing Measurement: Which Half?

A constant presence on today’s internet are ads. They power Google and Facebook and follow us everywhere. As with all marketing spend, they’re an investment. As with most investments, it’s crucial to measure their return. What makes online marketing different is the unprecedented possibility of building accurate measurement tools. In this post I’ll describe a … Read moreOnline Marketing Measurement: Which Half?

How to Identify Hotel Deals — Using Machine Learning

Web Scraping I used BeautifulSoup and Selenium in parallel to scrape 3 months of hotel listing information from Hotel.com. Some of the information I scraped were the checkin and checkout dates, number of adults and children, distance to city and convention centers, hotel addresses, hotel reviews and ratings, TripAdvisor’s ratings and reviews, hotel amenities, and … Read moreHow to Identify Hotel Deals — Using Machine Learning

STL decomposition : How to do it from Scratch?

Figure out what STL decomposition is and how it works. This article will help you understand what is STL decomposition and how to do it from scratch. At the end, I will use statsmodel library too, to get the results in seconds. So, STL stands for Seasonal and Trend decomposition using Loess. This is a … Read moreSTL decomposition : How to do it from Scratch?

Managerial Analytics and Data Science

Previously, we learned about two general areas of machine learning: Supervised and Unsupervised learning. Here, we’ll investigate two special fields of machine learning: time series prediction and natural language processing. Time Series Forecasting Time series forecasting refers to any type of supervised Machine Learning where time is an important feature. A good time series forecast … Read moreManagerial Analytics and Data Science

Enter Analytics: From Boot Camp to working in Data Science

We covered a lot in a short amount of time… almost too many topics, actually. Just when you start getting comfortable and ready to do more advanced things, they change the topic. It is really up to you to decide what direction you want to take things outside of the classroom. For example, I am … Read moreEnter Analytics: From Boot Camp to working in Data Science