Collaborating Authors

Understanding TF-IDF in NLP: A Comprehensive Guide


Natural Language Processing (NLP) is an area of computer science that focuses on the interaction between human language and computers. One of the fundamental tasks of NLP is to extract relevant information from large volumes of unstructured data. In this article, we will explore one of the most popular techniques used in NLP called TF-IDF. TF-IDF is a numerical statistic that reflects the importance of a word in a document. It is commonly used in NLP to represent the relevance of a term to a document or a corpus of documents.

Data Scientist at IT Concepts Inc. - Woodlawn, Maryland, United States


IT Concepts (ITC) is an 8(a) SDVOSB founded on the concepts of customer-centric, driven to deliver, teamwork, integrity, and innovation. Founded in 2003, ITC was established with a simple yet important promise to "deliver solutions that work". As we continue to grow in the support of our government customers, we are looking for driven and innovative individuals to join our team. IT Concepts is seeking a Data Scientist who will support several projects at a federal agency. The position is located in Woodlawn, MD.

Data Scientist, Liquidity Management at Stripe - Remote in United States, and Canada


Stripe is a financial infrastructure platform for businesses. Millions of companies--from the world's largest enterprises to the most ambitious startups--use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. This is one of the largest opportunities for impact in the history of computing, on par with the rise of modern operating systems.

10 of the best ChatGPT courses you can take for free this week


TL;DR: You can find a range of free ChatGPT courses(Opens in a new tab) on Udemy. Learn how to improve productivity, create unique and engaging content, and boost your business with the help of AI. We can't say for sure whether or not artificial intelligence will end up taking over, with human consciousness effectively replaced by the singularity, but we're excited to find out. If you're also looking to get an insight into this terrifying future, you can take a wide range of online artificial intelligence courses on Udemy. To get you started, we've found a bunch of beginner-friendly courses on ChatGPT.

Creating and editing with AI – Notion Help Center


The Notion AI Writing Suite will not use your data to train our models. Any information used to power Notion AI will be shared with our partners for the sole purpose of providing you with the Notion AI features. We do not allow any partners or 3rd parties to use your data for training their models or any other purpose.

Fourier Transformations Reveal How AI Learns Complex Physics


A new study has found that Fourier analysis, a mathematical technique that has been around for 200 years, can be used to reveal important information about how deep neural networks learn to perform complex physics tasks, such as climate and turbulence modeling. This research highlights the potential of Fourier analysis as a tool for gaining insights into the inner workings of artificial intelligence and could have significant implications for the development of more effective machine learning algorithms. Fourier transformations reveal how deep neural network learns complex physics. One of the oldest tools in computational physics -- a 200-year-old mathematical technique known as Fourier analysis -- can reveal crucial information about how a form of artificial intelligence called a deep neural network learns to perform tasks involving complex physics like climate and turbulence modeling, according to a new study. The discovery by mechanical engineering researchers at Rice University is described in an open-access study published in the journal PNAS Nexus, a sister publication of the Proceedings of the National Academy of Sciences.

Hyperparameter Optimization -- Intro and Implementation of Grid Search, Random Search and Bayesian Optimization


Usually the first solution that comes to mind when trying to improve a machine learning model is to just add more training data. Additional data usually helps (barring certain situations) but generating high-quality data can be quite expensive. Hyperparameter optimization can save us time and resources by getting the best model performance using the existing data. Hyperparameter optimization, as the name suggests, is the process of identifying the best combination of hyperparameters for a machine learning model to satisfy an optimization function (i.e. In other words, each model comes with multiple knobs and levers that we can change, until we get to the optimized combination.

CSIRO launches Responsible AI Network - ABC News


The new platform brings together a range of professions to teach industry how to utilise resources within the data arena using artificial intelligence tools ethically.

Why are we debating Crypto vs. Artificial Intelligence?


The great debate of "crypto vs artificial intelligence" is heating up in 2023, but I don't think it deserves to be scrutinized in a negative manner. Debates like these come naturally with all emerging technology. Remember the famous headline about the internet? "Internet'may be just a passing fad as millions give up on it,'" reads Daily Mail in December 2000. Blockchain is a decentralized, immutable ledger that facilitates a secure and transparent exchange of encrypted data shared across a network where information is available to all participants simultaneously.

Uncovering the Mystery of AI Learning with Fourier Transformations - Bytefeed - News Powered by AI


Fourier Transformations are a powerful tool for understanding how Artificial Intelligence (AI) learns complex physics. By using Fourier transformations, researchers can gain insight into the inner workings of AI and its ability to learn from data. The Fourier transformation is a mathematical technique used to decompose signals into their component frequencies. It has been used in many areas of science, including signal processing, image analysis, and quantum mechanics. In recent years, it has also become an important tool for studying AI algorithms.