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Image Source: https://www.digitalocean.com/ Around the Universe Typing “what is machine learning?” into a Google search opens up a pandora’s box of forums, academic research, and here-say — and the purpose of this article in the 101 for Dummies like Me series is to simplify the definition and understanding of machine learning. In addition to an … Read more Machine Learning 101 for Dummies like Me

Hanabi is a new game that combines cooperation between players with imperfect information. Earlier this year, researchers from DeepMind and Google published a paper proposing the game of Hanabi as the new frontier for artificial intelligence(AI) agents. The reason for the designation is that Hanabi combines many of the most difficult challenges for AI models … Read more Facebook Builds an AI Agent to Master the Hanabi Challenge: The New Frontier for AI Research

Using Go and PostgreSQL to analyze a year of streaming. By now, Spotify users everywhere have gotten their 2019 Wrapped results. I wasn’t too surprised by mine, partly because I knew I’d spent a lot of time exercising to music by a soon-to-be-returning band from the 90s, but also because I’d recently used Spotify’s privacy … Read more I wrapped my Spotify history the hard way.

Power BI is really growing on me. Using this software everyday, I am amazed by the capabilities of this product and the way it improves month after month by adding new features or optimizing current capabilities. However, like any software solution, there is still room for improvement and a lack of some features that would … Read more Power BI: Implement AND/OR Selection

Should we use the mean or median? After seeing my beloved Hawthorn Hawks tweet out an article on their website regarding player ages for each team, it got me riled up that the media love to cite Champion Data’s “average age” as their measure. As can be seen with the age distribution of players as … Read more When the statistic used changes the AFL age narrative for 2020

Enterprise Data Science is much more than Data Science Aerial Target Interdiction Archives: California Tactical Academy Who is your customer? Earlier this year I sat in on a presentation featuring an aircraft that will “possibly” replace the Boeing V-22 Osprey. The V-22 Osprey is a multi-mission military aircraft that has been in active military service … Read more The Single Strategy You Need to find your Development Target

Thinking further ahead, I found that the logistic regression model would be unable to utilize incremental learning later in the project, while the linear SVM (powered by sklearn’s SGDClassifier()) would. The accuracy trade-off was small with the logistic regression having an average F1-score of 93%, while the SVM having an average F1-score of 92%. Thus, … Read more Building and Deploying a Data Science Project in Two weeks

The Advantages and Disadvantages of Deep Learning Implementation Faced by Today’s Businesses and Organizations. Image Source: Pixabay Deep learning has two key strengths that set it apart from other machine learning techniques. The first of these is feature learning. With other techniques, data scientists manually transform features to get the best results with a particular … Read more Eight Deep Learning Pros and Cons

How to deploy a trained ML model behind a Flask API on the internet. Coming from a software development background I never thought twice about productionizing my models. But for anyone just getting into coding, as a data scientist, it may not be obvious. For a model to be used in the real world, you’ll … Read more Productionize a Machine Learning model with Flask and Heroku

I love Physics. And if only I hadn’t developed the taste to live my professional life outside of university campus labs, I would have continued on the course. At some point in my life, however, I sensed I would enjoy the lifestyle that many software developers have. Naturally, Data Science seemed like the best of … Read more Can Data Science get inspiration from Physics?

Detecting regions of Neanderthal ancestry with Deep Learning This is the seventh post of my column Deep Learning for Life Sciences where I give concrete examples of how Deep Learning can already now be applied in Computational Biology, Genetics and Bioinformatics. In the previous posts, I demonstrated how to use Deep Learning for Ancient DNA, … Read more Deep Learning on Neanderthal Genes

A Framework & Package That Ease the Pain Source: ThremoFisher Scientific Three weeks into my journey to become a data scientist and I’ve officially been baptized… by fire, that is! I chose to attend Flatiron’s Data Science 15-week bootcamp to transition out of finance. So far, the program has exceeded expectations (and my expectations were … Read more Missing Data?

R for Industrial Engineers Exploring the “SixSigma” R package Image by Lenny Kuhne available at Unsplash Process capability analysis represents a significant component of the Measure phase from the DMAIC (Define, Measure, Analysis, Improve, Control) cycle during a Six Sigma project. This analysis measures how a process performance fits the customer’s requirements, which are translated … Read more Process Capability Analysis with R

Image adapted from shap.readthedocs.io For insight into Shapley values and the SHAP tool. Most other sources on these topics are explanations ased on existing primary sources (e.g. academic papers and the SHAP documentation). This post is an attempt to gain some understanding through an empirical approach. To learn about an alternative approach to computing Shapley … Read more A new perspective on Shapley values: the Radical Shapley method

Understanding the effect of random states on model outcome Tuning hyperparameters, performing the right kind of feature engineering, feature selection etc are all part of the data science flow for building your machine learning model. Hours are spent tweaking and modifying each part of the process to improve the outcome of our model. However, there … Read more Manipulating machine learning results with random state

Now, let’s have a bird’s-eye view of the listings distribution across Kuala Lumpur. As you can see, most of the Airbnb listings are accumulated in the city center area of Kuala Lumpur. That’s why the price of the listings are lower in the city area as supply is much higher. Feel free to navigate the … Read more How to invest in the best Airbnb rental property

What if I ask you to think about data science work? Chances are that images of notebooks, data plots, algorithms and programming snippets pop into your mind. When talking about this sort of work very often we focus on tools and techniques useful for specific tasks ranging from things like classification or NLP, through cool … Read more From Business Needs to Data Science Tasks

Improving model sensitivity and accuracy by attaching attention gates on top of the standard U-Net Medical image segmentation has been actively studied to automate clinical analysis. Deep learning models generally require a large amount of data, but acquiring medical images is tedious and error-prone. Attention U-Net aims to automatically learn to focus on target structures … Read more Biomedical Image Segmentation: Attention U-Net

Michael Kratsios CTO of the United States and Regulating AI An initiative that I think is great and that must be commended by the Institute for Human-Centered Artificial Intelligence at Stanford University is the sharing of videos spanning the entirety of their fall conference on AI Ethics, Policy and Governance. The two long videos, each … Read more A Cleaner Regulatory Approach to AI?

Photo by Philipp Lublasser on Unsplash With the 2020 Presidential election being within a year away, all the chatter on the news that’s not about impeachment has been about who’s going to be the Democratic Candidate to face President Trump. Existing information sources that include news outlets and polls exist but to me personally, I … Read more Does YouTube’s Data Tell Us A Story About The 2020 Democratic Candidates?

With the map shapes prepped, I’m ready to put that pet data to use! Take away #3: Geopandas.plot() uses pretty much all the argument’s you know and love from matplotlib.pyplot First, I added the new intersection geometries determined in the last step to my GeoDataFrame. Note: Geopandas always plots the “geometry” column by default to … Read more Puppies & Python: Analyzing Geospatial Data

Businesses should be using data to optimize processes, increase efficiency, and accelerate innovation. Image Source: UnSplash According to Gartner, In 2010, the number of large enterprises with a Chief Data Officer (CDO) was 15. By 2017, it was up to 4,000. In 2020, it’ll be over 10,000. Those numbers are remarkable, but does the sheer … Read more The Importance of Data-Intelligence for Businesses

Now, what if I wanted to compare James Harden’s forecast to Giannis Antetokounmpo, LeBron James, and Kawhi Leonard. To do this, I’ll take all of the pre-processing and put it in a single function, so I can pre-process the data without repeating lines of code. Below, I’ve supplied a gist that contains the required functions. … Read more The Fastest and Easiest Way to Forecast Data on Python

Transformation, oversight, governance. security and transparency are all paramount as the industry continues to evolve. Image Source: Pixabay This piece will inform policies and actions for AI to be fully productive and beneficial, and enable your organization to build and deploy AI models that have integrity and transparency. At stake are business outcomes — and … Read more Five Steps to Ethical AI for Businesses

The convolution for RGB images is quite similar to the grey-scale case. The equation 4 can be adapted to RGB image adding another loop to iterate over the RGB channels as follows: The additional loop over the variable 𝑐 allows the iteration on the channels RBG. As a result, the sum is done over three-dimensional … Read more Visualizing the Fundamentals of Convolutional Neural Networks

Exploratory Data Analysis of the bicyclists counts data set The following table contains counts of bicyclists traveling over various NYC bridges. The counts were measured daily from 01 April 2017 to 31 October 2017. We’ll focus on the counts on the Brooklyn bridge. Source: Bicycle Counts for East River Bridges (NYC OpenData) I have cut … Read more Fitting Linear Regression Models on Counts Based Data

Resolving a fundamental conflict between classical statistics and modern ML advice Photo by Franki Chamaki on Unsplash I recently came across a very interesting paper written at OpenAI on the topic of deep double descent. The paper touches at the very nature of training machine learning systems and model complexity. I hope to summarize the … Read more Deep Double Descent: when more data and bigger models are a bad thing

The year is coming to an end, and if any of you work in the relevant departments of the company’s financial accounting, you must be busy preparing various annual financial statements. Especially for beginners who have just entered this field, how to design reports to clearly show the financial analysis and business operation status is … Read more 6 Data Analysis Methods to Help You Make Great Financial Statements

What I learned from analyzing 300K German online deals Every year on Black Friday, people try to find the best deals hoping to save a ton of money. In the U.S. the Black Friday craziness has even lead to 12 deaths and 117 injuries thus far. If you are like me and prefer to do … Read more Data Science and Black Friday: When, how and where to find the best deal?

Data science is a very hands-on and practical field. Data science requires a solid foundation in mathematics and programming. As a data scientist, it is essential that you understand the theoretical and mathematical foundations of data science in order to be able to build reliable models with real-world applications. In data science and machine learning, … Read more Theoretical Foundations of Data Science— Should I Care or Simply Focus on Hands-on Skills?

Comparing models in a social media NLP challenge. Zen and the Art of Motorcycle Maintenance was one of my favorite books in college. Set amidst a father-son motorcycle journey across the United States, the book considers how to lead a meaningful life. Arguably, the key message expounded by the author, Robert Pirsig, is that we … Read more Zen and the Art of Model Optimization: Comparing models in a social media NLP challenge

Artificial Intelligence (AI) is a complex and evolving field. The first challenge an AI aspirant faces is understanding the landscape and how he could navigate through it. Consider this, if you are travelling to a new city, and if you don’t have the map, you will have trouble to navigate the city and you will … Read more How to Navigate Artificial Intelligence Landscape?

Exploring the Definition of Bias in AI When the word ‘data’ is talked about in artificial intelligence ‘bias’ is often mentioned alongside the given discussion. I will have a general discussion of bias first that will be related to subjectivity and objectivity. Whereafter I will return to a summary of things to consider in relation … Read more Subjective and Objective in the Development of Artificial Intelligence

Mean Reversion with Bollinger bands gone wrong Photo by Rick Tap on Unsplash A few years ago we did some work with a Trading simulation. Our strategy was Mean Reversion with Bollinger Bands. Thankfully, it was only a simulation as the losses from share variations and software bugs were horrific. In this article we offer … Read more Algorithmic trading

And build a great mathematical foundation Photo by Antoine Dautry on Unsplash Awhile back I wrote an article on the top books to get started with data science: The Top 3 Books to Get Started with Data Science Right Now And build a great foundation of knowledge towardsdatascience.com One of the readers left a comment … Read more The Top 3 Books to Learn Math for Data Science Right Now

Why does management need to observe data-science-related KPIs? Binoculars Man, Pixabay. Observability for data-science (DS) is a new and emerging field, which is sometimes mentioned in tandem with MLOps or AIOps. New offerings are being developed by young startups to address the lack of monitoring and alerts for everything data-science. However, they are mostly addressing … Read more Data-Science Observability For Executives

In the current business climate, application modernization represents both a significant opportunity and a technological challenge. Image Source: Pixabay In today’s digital economy, organizations that run legacy applications run the risk of being disrupted and putting themselves in a profoundly uncompetitive position. Those with an agile environment, hosting core apps on the hybrid Cloud, are … Read more How and Why Businesses Should Modernize Applications

As usual, let’s first load the data. For this exercise, we will use Boston housing data available in sklearn.datasets. Loading the Boston data and splitting it into training and testing dataframe Now, to accomplish model averaging, we will use RMSE (root mean squared error) as the model fitness. Then we will average them using the … Read more Model Averaging: A Robust Way to Deal with Model Uncertainty

What you must put in place to achieve tangible success using machine learning and artificial intelligence technologies. Image Source: Pixabay AI can provide a host of benefits for the enterprises and organizations of today. From understanding customer behavior to fraud detection, visualizing analytical sentiments, and predicting machine failure. Machine learning, if implemented efficiently, promises to … Read more 4 Ways to Successfully Scale AI and Machine Learning for Businesses