Special topics in machine learning
Algorithmia is machine learning, managed. Deploy, serve, and manage your ML portfolio.
11 September 2020
4 min read
A machine learning framework is an interface that allows developers to build and deploy machine learning models faster and easier. A tool like this allows enterprises to scale their machine learning efforts securely while maintaining a healthy ML lifecycle. read more
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19 December 2019
3 min read
Simplifying model deployment  Deploying models should be an uncomplicated endeavor. To that end, Algorithmia continually aims to ensure machine learning’s value is seen, which means getting to model deployment as quickly and as painlessly as possible. Fortunately, there are many paths to get there. A...
17 December 2019
6 min read
As more organizations incorporate AI and machine learning in to their processes, data scientists and analysts must continue to learn about how these techniques solve business problems. Previously on this blog we discussed how particular algorithms may be more appropriate for particular research questions...
13 December 2019
5 min read
Types of machine learning Machine learning comes in three basic types: supervised, unsupervised, and reinforcement learning. Reinforcement learning follows a different paradigm from the other two, so we’ll leave it for another post.  The most common form of machine learning, and the most prototypical,...
10 December 2019
4 min read
Demand forecasting is a common business practice for optimizing workflow in inventory, but it  actually has use cases across all industries even if it isn’t immediately clear. Let’s walk through how demand forecasting can be used and explore its value.    What is demand forecasting? Demand forecasting...
6 December 2019
6 min read
Machine learning is a vast field, composed of many model types, subsets, and use cases. In our forthcoming 2020 State of Enterpriser Machine Learning report, we dig into the use cases that are used most often by businesses today, but as there are new advances made in ML every day, there are also advances...
4 December 2019
4 min read
Read it Reflects data only from survey Group B. Respondents were allowed to choose more than one answer. In the last 12 months, there have been numerous developments in machine learning (ML) tools, applications, and hardware. Google’s TPUs are in their third generation, the AWS Inferentia chip is a...
29 November 2019
10 min read
Sentiment analysis invites us to consider the sentence, You’re so smart! and discern what’s behind it. It sounds like quite a compliment, right? Clearly the speaker is raining praise on someone with next-level intelligence. However, consider the same sentence in the following context. Wow,...
25 November 2019
6 min read
(Wikispecies) R is an excellent language for machine learning. R primarily excels in the following three areas: Data manipulation Plotting Built-in libraries R manipulates data using a native, in-built data structure called a data frame. Let’s load some data now and see how R can help us to...
22 November 2019
5 min read
Recently, Algorithmia ventured from Seattle to London to discover what was happening at the Big Data London (BDL) conference in Kensington. We had great conversations with data engineers, data analysts, and business leaders about how Algorithmia makes it easy to deploy machine learning models into production....
20 November 2019
6 min read
(Depiction of a clustering model, Medium) Getting started with machine learning starts with understanding the how and why behind employing particular methods. We’ve chosen five of the most commonly used machine learning models on which to base the discussion. AI taxonomy  Before diving too deep,...