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Why Do Companies Use Data Lakes?
/0 Comments/in Data Engineering, Data Warehousing /by Philip PileticModern enterprise-level computing operations have to capture a truly monumental amount of information every single hour. As the scale of data has grown almost exponentially over the years, so has the scale and complexity of data stores. Traditional databases couldn’t possibly keep up with the massive numbers of records that have to be created today, […]
Understanding the “simplicity” of reinforcement learning: comprehensive tips to take the trouble out of RL
/0 Comments/in Artificial Intelligence, Data Science, Deep Learning, Machine Learning, Main Category /by Yasuto Tamura*I adjusted mathematical notations in this article as close as possible to “Reinforcement Learning:An Introduction.” This book by Sutton and Barto is said to be almost mandatory for those who studying reinforcement learning. Also I tried to avoid as much mathematical notations, introducing some intuitive examples. In case any descriptions are confusing or unclear, informing […]
The Basics of Logistic Regression in Data Science
/0 Comments/in Data Science /by Shannon FlynnData science is a field that is growing by leaps and bounds. A couple decades ago, using a machine learning program to make predictions about datasets was the purview of science fiction. Today, all you need is a computer, some solid programming, and a bit of patience, and you, too, can have your own digital […]
Why Your Data Science Team Needs Separate Testing, Validation & Training Sets
/0 Comments/in Data Science /by Philip PileticAutomated testing of machine learning models can help to dramatically reduce the amount of time and effort that your team has to dedicate to debugging them. Not applying these techniques properly, however, could potentially do a great deal of harm if the process is completely unmonitored and doesn’t adhere to a list of best practices. […]
My elaborate study notes on reinforcement learning
/0 Comments/in Artificial Intelligence, Data Science, Data Science Hack, Deep Learning, Machine Learning, Main Category, Use Cases /by Yasuto TamuraI will not tell you why, but all of a sudden I was in need of writing an article series on Reinforcement Learning. Though I am also a beginner in reinforcement learning field. Everything I knew was what I learned from one online lecture conducted in a lazy tone in my college. However in the […]
AI Platforms – A Comprehensive Guide
/0 Comments/in Tool Introduction /by Jaimin DaveA comprehensive guide compiled to introduce readers to AI platforms, their types, and benefits. A concluding section to discuss AI platform selection strategy with Attri’s Best of Breed approach to build AI platforms. Don’t you think that this century is really fortunate? In my opinion, the answer is yes; we witnessed technological transformations and their […]
How to Successfully Perform a Data Quality Assessment (DQA)
/0 Comments/in Business Analytics, Data Migration, Data Warehousing /by Shannon FlynnPeople generate 2.5 quintillion bytes of data every single day. That’s 1.7 megabytes generated every second for each of the 7.8 billion residents of Earth. A lot of that information is junk that somebody can easily discard, but just as much can prove to be vital. How do you tell the difference? According to industry […]
Coffee Shop Location Predictor
/0 Comments/in Data Mining, Data Science, Data Science Hack, Main Category, Predictive Analytics, Python, Tutorial, Visualization /by Mrinalini SunderAs part of this article, we will explore the main steps involved in predicting the best location for a coffee shop in Vancouver. We will also take into consideration that the coffee shop is near a transit station, and has no Starbucks near it. Well, while at it, let us also add an extra feature […]
What Is Data Lake Architecture?
/0 Comments/in Data Engineering, Data Warehousing /by Shannon FlynnThe volume of information produced by everyone in the world is growing exponentially. To put it in perspective, it’s estimated that by 2023 the big data analytics market will reach $103 billion. Finding probable solutions for storing big data is a challenge. It’s no easy task to hold enormous amounts of information, clean it and […]
How Microsoft Azure Is Impacting Financial Companies
/0 Comments/in Cloud, Insights, Use Cases /by Renata KalsbeekMicrosoft Azure has taken a large chunk of the cloud marketplace, transforming companies with the speed and security of the cloud. Microsoft has over the years used Azure to cushion companies against risk, deal with fraud and differentiate their customer experience. With Microsoft Cloud App Security, customers experience 75% automatic threat elimination because of increased […]