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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... Read more
What are MLOps and Why Does it Matter?
During the industrial revolution, the rise of physical machines required organizations to systematize, forming factories, assembly lines, and everything we know about automated manufacturing. During the first tech boom, Agile systems helped organizations operationalize the product lifecycle, paving the way for continuous innovation by clearing waste... Read more
How to Choose Machine Learning or Deep Learning for Your Business
AI is the future, or so you’re hearing. Every day, news of another organization leveraging AI to produce business outcomes that outstrip competition hit your inbox, but your company either hasn’t started at all or is mired in the discussion. AI, machine learning, and deep learning... Read more
25 Excellent Machine Learning Open Datasets
Editor’s note: There is an updated version of this article for 2021. Please read it here for the most up-to-date listing on machine learning datasets! Your machine learning program is only as good as your training sets. Data sets are an integral part of the quality... 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... Read more
Properly Setting the Random Seed in ML Experiments. Not as Simple as You Might Imagine
Join Comet at Booth 406 in the ODSC East Expo Hall. We will also be speaking at ODSC: – April 30, 9 am — A Deeper Stack for Deep Learning: Adding Visualizations + Data Abstractions to your Workflow (Douglas Blank, Head of Research) – May... Read more
4 Steps to Start Machine Learning with Computer Vision
In 2012, AlexNet took first place at the ImageNet Large Scale Visual Recognition Challenge, marking the first time a convolutional neural network had won the image classification competition. One more factor that made this achievement much more significant is that AlexNet showed twice the accuracy than... 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... Read more
Machine Learning Challenges You Might Not See Coming
There seems to be a skills gap, and a skills misunderstanding, when it comes to Data Science, Engineering, and DevOps as a joint process. At our machine learning consultancy, Infinia ML, we view deployment as a sequential process across teams: (1) Data Science explores data and... Read more
Identifying Poisonous Mushrooms with Rule Learners
Each year, many people fall ill and sometimes even die from ingesting poisonous wild mushrooms. Since many mushrooms are very similar to each other in appearance, occasionally even experienced mushroom gatherers are poisoned. If simple, clear, and consistent rules were available for identifying poisonous mushrooms, they... Read more