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An Introduction to Apache, PySpark and Dataframe Transformations

A Comprehensive Guide to Master Big Data Analysis Introduction: The Big Data Problem Apache arises as a new engine and programming model for data analytics. It’s origin goes back to 2009, and the main reasons why it has gained so much importance in the past recent years are due to changes in

19 entities for 104 languages: A new era of NER with the DeepPavlov multilingual BERT

There’s hardly anyone left in the world data science community who wouldn’t agree that the release of BERT was the most exciting event in the NLP field. For those who still haven’t heard: BERT is a transformer-based technique for pretraining contextual word representations that enables state-of-the-art results across a wide

Traditional vs Deep Learning Algorithms used in BlockChain in Retail Industry — III

SecureSVM, Boosting, Bagging, Clustering, LSTM, CNN, GAN Introduction In continuation to my previous blogs, “Traditional vs Deep Learning in Retail Industry” and “Deep Learning Vs Deep Reinforcement Learning Algorithms in Retail Industry” this blog highlights on different ML algorithms used in blockchain transactions with a special emphasis on bitcoins in retail

Beyond Bar Graphs and Pie Charts

A BEGINNER’S GUIDE Using Python, R, Tableau, and RawGraphs to effectively and beautifully communicate your data I understand. Maybe you forgot about your presentation this afternoon. Maybe you have 5 minutes to throw together the 3 visuals your boss wants on his desk by the end of the day. Maybe

Artificial Intelligence Made Easy

Photo Source: ShutterStock A Comprehensive Guide to Modeling with in Python By Ishaan Dey & Elyse Lee If you’re anything like my dad, you’ve worked in IT for decades but have only tangentially touched data science. Now, your new C-something-O wants you to fire up a data analytics team and

Convolutional Neural Networks: an Introduction (TensorFlow Eager API)

Keep an eye out for Deep Learning. Source: Pixabay. Convolutional Neural Networks are a part of what made Deep Learning reach the headlines so often in the last decade. Today we’ll train an image classifier to tell us whether an image contains a dog or a cat, using TensorFlow’s eager API.

Machine Learning: Lessons Learned from the Enterprise

Photo by IBM There’s a huge difference between the purely academic exercise of training Machine Learning (ML) models versus building end-to-end Data Science solutions to real enterprise problems. This article summarizes the lessons learned after two years of our team engaging with dozens of enterprise clients from different industries including manufacturing,

Replacing VBA with Java in Excel

Excel is ubiquitous in nearly every workplace. From top tier investment firms and large scale engineering companies right down to individual sole traders, people get work done using Excel. This article will look at some of the problems and advantages of using Excel, and how using Java embedded in Excel

Dynamically split/create multiple datasets from single dataset in SAS

Splitting a dataset into multiple datasets is a challenge often faced by SAS programmers. For example, splitting data collected from all over the world into unique country-wise datasets, where each datsaset contains data specific only to that country. In such scenarios, programmers are often forced to hard code the program

Promoting Energy and Economic Empowerment with Python

Renewable energy can play a key role when comes to empowering people. I created a tool to do solar power simulations over a 20 year time and tested it on my city, Porto, with several values of electricity average monthly bills. The goal is to give, for each average monthly