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How to Use Deep Learning to Write Shakespeare
LSTM recurrent neural networks can be trained to generate free text. Let’s see how well AI can imitate the Bard “Many a true word hath been spoken in jest.” ― William Shakespeare, King Lear   “O, beware, my lord, of jealousy; It is the green-ey’d monster, which doth mock The... Read more
The Complete Guide to Decision Trees (part 1)
In the beginning, learning Machine Learning (ML) can be intimidating. Terms like “Gradient Descent”, “Latent Dirichlet Allocation” or “Convolutional Layer” can scare lots of people. But there are friendly ways of getting into the discipline, and I think starting with this guide to decision trees is a wise decision.... Read more
5 Roadblocks to Getting an ML System in Production
We typically meet an organization’s data science team after they’ve carried out a successful proof of concept. The algorithm they built or acquired produced results that were promising enough to greenlight development of a production ML system. It’s at this point that the immaturity of ML project management often... Read more
Learn How to Organize, Cleanup and Process Medical Image Datasets for Computer Vision Training
We are entering a whole new world where the possibility for AI, and more specifically computer vision, can help us with medical decision making that we’ve relied on doctors to perform. Moreover, while the hope of having doctor-less diagnoses is still a work of science fiction, every day we... Read more
ODSC East DeepOps: Building an AI First Company
I’ve spoken to over a hundred AI companies as part of my job at MissingLink.ai and the result of analyzing their experiment, data and compute workflows. Certain challenges were a common theme across many teams – the solutions to these is a concept we call “DeepOps”, deep learning operations.... Read more
Darwin: Machine Learning Beyond Predefined Recipes
The same way a tailored suit feels and looks different from generic options because it actually fits, tailored models perform differently than pre-established boxed algorithms because they are custom-fitted to your data. To answer this need, SparkCognition has developed Darwin™, a machine learning product that automates the building and... Read more
Being Open in the Era of Privacy
When Netflix announced a 1 million dollar challenge for improving their recommendation engine, together with releasing 100 million movie ratings in 2006, they knew little what would happen next. Netflix has been working on a recommender system for years by then, were recognized for their business innovation as well... Read more
Help Set the Standards for Analytics Professionals For a Chance to Win Data Science Gifts
As the role of data and analytics is expanding rapidly in creating new business models or changing existing ones, demand for analytics professionals is growing at an increasing rate. The world has witnessed an explosion in the number of people describing themselves as data scientists or analytics professionals. This... Read more
All The Cool Things You Can Do With PostgreSQL for Data Analysis
We all know that one of the biggest tasks is cleaning our data and getting it ready for analysis. Once you’ve spent all that time cleaning your data I will argue you should store it in a relational database. While you may not do all your analysis there –... Read more
Why Do Tree Ensembles Work?
Ensembles of decision trees (e.g., the random forest and AdaBoost algorithms) are powerful and well-known methods of classification and regression. We will survey work aimed at understanding the statistical properties of decision tree ensembles, with the goal of explaining why they work. An elementary probabilistic motivation for ensemble methods... Read more