This article was published as a part of the Data Science Blogathon. Introduction Modern applications are popularly made using container orchestration systems and microservice architecture. In 2014, the first echoes of the word Kubernetes in tech were heard, and the conquest of Kubernetes is due in no small amount to its flexibility and authority. Back […]
In this article, we will take a look at another possible methodology to make decisions at a more minute level, that is Fuzzy logic systems.
Technical content translation may seem like an easy task at first but once you actually start doing it, you will quickly change your mind. There are certain procedures and rules in technical translation that do not necessarily apply to regular kinds of translation. You need to understand these special requirements so that you can create …
As you adopt a DataOps strategy to help make your business a data business, here are four key things to keep in mind.
Understand the reasoning and inner works behind machine learning models and AI use the LIME algorithm; explain and interpret Named Entity Recognition
Explainable Named Entity Recognition is a concept of making Named Entity Recognition more explainable and interpretable.
A simple, yet powerful, optimization technique that will make your programs run about 2.5 times faster
Want to learn how to use Kaldi for Speech Recognition? Check out this simple tutorial to start transcribing audio in minutes.
This article was published as a part of the Data Science Blogathon. Introduction to Deep Learning Artificial Intelligence, deep learning, machine learning — whatever you’re doing if you don’t understand it — learn it. Because otherwise you’re going to be a dinosaur within 3 years. -Mark Cuban This statement from Mark Cuban might sound drastic – but its message is […]
In this tutorial we will leverage Rubrix and cleanlab to find, uncover and correct potential label errors. You can do this following 4 basic steps: ð¾ load a dataset with potential label errors, her...
Caveats of Compare Functions in C++
This article will introduce you to the programming languages you should choose to learn in 2022. Programming Languages to Learn in 2022.
GPT-3 is an exceptional mimic. It looks at the text input and attempts to respond with what text it thinks best completes the input. If the first line sounds like something from a romance novel it …
Ontologies and Semantic Annotation. Part 1: What Is an Ontology In the abundance of information, both machines and human researchers need tools to navigate and process it. Structuring and formalization of data into hierarchies, such as trees, may establish the relations between the data required for efficient machine processing and may make the information more… Read More »Ontologies and Semantic Annotation. Part 1: What Is an Ontology
In the previous part, we started to outline what ontologies are and how they may be used; now it is time to get into more practical guidelines and tips that would help build an ontology from scratch. Though there exist a number well-established methodologies for developing an ontology in various environments, including Protege, Ontolinqua and… Read More »Ontologies and Semantic Annotation. Part 2: Developing an Ontology
Avoid a Hard Reboot for Ubuntu
Avoid a Hard Reboot for Ubuntu
In 2011 the New York City Council passed Local Law #12 requiring the NYPD to collect and make available to the public records of all…
Learn how to perform real-time speech recognition with Python in 3 steps.
Quite a while back, I had written a post in which I described how to package your Machine Learning models using Docker and deploy them using Flask. This post, through a PoC, describes - How to package your model using Docker (similar as last post) How to push the Docker container to Amazon ECR Add a Lambda Function for your model Make a REST API using Amazon API Gateway to access your model Automate the whole process using Github Actions, so that any updates to the model can take effect immediately Make a Streamlit app to make a UI to access the REST API (for the model deployed on AWS) All the code can be found in my Github repository.
Answer (1 of 5): As Ian Goodfellow mentions, one way is to restrict the loss function to a line. The gist is this: you take a random 1-D slide of the function arguments and plot it against the objective function values. Then, simply plot many random 1-D slices and the instance that you find a sli...
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