Special topics in machine learning
Algorithmia is machine learning, managed. Deploy, serve, and manage your ML portfolio.
11 August 2020
5 min read
Semi-supervised learning is the type of machine learning that uses a combination of a small amount of labeled data and a large amount of unlabeled data to train models. This approach to machine learning is a combination of supervised machine learning, which uses labeled training data, and unsupervised... read more
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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,...
19 November 2019
5 min read
Every year, millions of dollars are wasted planning, cleaning, and training machine learning (ML) models that will never get to production. This means that more than half of data science projects are not fully deployed—and some never will be, resulting in zero generated revenue. When organizations...
13 November 2019
3 min read
Meet with us! AWS re:Invent is next month, and we are pleased to announce that Algorithmia CEO, Diego Oppenheimer, will be speaking on the new software development lifecycle (SDLC) for machine learning. Often we get variations on this question: how can we adapt our infrastructure, operations, staffing,...
7 November 2019
5 min read
Why is churn prediction important?  Defined loosely, churn is the process by which customers cease doing business with a company. Preventing a loss in profits is one clear motivation for reducing churn, but other subtleties may underlie a company’s quest to quell it. Most strikingly, the cost of...