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Algorithm Computer Science Natural Language Processing 
Dataconomy
APRIL 21, 2025
Natural language processing (NLP) is a fascinating field at the intersection of computer science and linguistics, enabling machines to interpret and engage with human language. What is natural language processing (NLP)? Delivering insightful analyses from varied textual sources.
Analytics Vidhya
DECEMBER 30, 2022
Introduction Natural language processing (NLP) is a field of computer science and artificial intelligence that focuses on the interaction between computers and human (natural) languages. Natural language processing (NLP) is […].
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Dataconomy
SEPTEMBER 16, 2024
Considering that some languages, notably English, seem to dominate digitally, there is actually a tremendous need for tools that can work across different languages and carry out diverse tasks. Over the past few years, numerous tools have emerged based on multilingual models for natural language processing (NLP).
Mlearning.ai
JANUARY 26, 2023
Introduction Natural language processing (NLP) sentiment analysis is a powerful tool for understanding people’s opinions and feelings toward specific topics. NLP sentiment analysis uses natural language processing (NLP) to identify, extract, and analyze sentiment from text data.
MAY 21, 2023
In recent times, Large Language Models (LLMs) have evolved and transformed Natural Language Processing with their few-shot prompting techniques. …
Defined.ai blog
SEPTEMBER 21, 2023
That’s the power of Natural Language Processing (NLP) at work. In this exploration, we’ll journey deep into some Natural Language Processing examples , as well as uncover the mechanics of how machines interpret and generate human language. What is Natural Language Processing?
Heartbeat
FEBRUARY 8, 2023
Source: Author The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities.
Data Science Dojo
JULY 4, 2023
Generative AI harnesses deep learning algorithms to generate human-like data in response to user input. This technology finds applications in NLP, computer vision, autonomous driving, robotics, and more. Back to basics: What is Generative AI? It goes beyond traditional programming, empowering machines with creativity and curiosity.
195 
Dataconomy
MAY 29, 2023
Explanation of AI and ML Artificial Intelligence (AI) refers to a field within computer science dedicated to the creation of intelligent machines, capable of executing tasks typically requiring human intelligence. These algorithms allow AI systems to recognize patterns, forecast outcomes, and adjust to new situations.
Dataconomy
FEBRUARY 27, 2025
Background and interdisciplinary approach Various disciplines contribute to the development and understanding of neuromorphic computing. Current projects focus on refining hardware and algorithms to maximize energy efficiency and processing capabilities in neuromorphic systems.
DrivenData Labs
MAY 18, 2023
I work on machine learning for natural language processing, and I’m particularly interested in few-shot learning, lifelong learning, and societal and health applications such as abuse detection, misinformation, mental ill-health detection, and language assessment. How did you get started in data science?
Dataconomy
APRIL 4, 2025
Understanding of AI, ML, and NLP A strong grasp of machine learning concepts, algorithms, and natural language processing is essential in this role. Skills and requirements for AI prompt engineers To succeed as an AI prompt engineer, individuals need a specific set of skills and knowledge bases.
91 
Smart Data Collective
MARCH 27, 2023
Data Scientists and Analysts use various tools such as machine learning algorithms, statistical modeling, natural language processing (NLP), and predictive analytics to identify trends, uncover opportunities for improvement, and make better decisions. as this will set you apart from other applicants.
119 
Pickl AI
JULY 18, 2023
With technological developments occurring rapidly within the world, Computer Science and Data Science are increasingly becoming the most demanding career choices. Moreover, with the oozing opportunities in Data Science job roles, transitioning your career from Computer Science to Data Science can be quite interesting.
Pickl AI
DECEMBER 26, 2024
Introduction In recent years, two technological fields have emerged as frontrunners in shaping the future: Artificial Intelligence (AI) and Quantum Computing. A study demonstrated that quantum algorithms could accelerate the discovery of new materials by up to 100 times compared to classical methods.
AWS Machine Learning Blog
MARCH 21, 2025
million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Generate metadata Using natural language processing, you can generate metadata for the paper to aid in searchability.
116 
AWS Machine Learning Blog
JANUARY 21, 2025
SageMaker Canvas supports multiple ML modalities and problem types, catering to a wide range of use cases based on data types, such as tabular data (our focus in this post), computer vision, natural language processing, and document analysis. Choose Save.
102 
NYU Center for Data Science
JULY 18, 2023
MaD & MaD+ The Math and Data (MaD) group is a collaboration between CDS and the NYU Courant Institute of Mathematical Sciences. And how can we best use insights from natural intelligence to develop new, more powerful machine intelligence technologies that more fruitfully interact with us?”
98 
Dataconomy
APRIL 18, 2023
The basics of artificial intelligence include understanding the various subfields of AI, such as machine learning, natural language processing, computer vision, and robotics. Additionally, it is crucial to comprehend the fundamental concepts that underlie AI, including neural networks, algorithms, and data structures.
Pickl AI
DECEMBER 25, 2024
Data Science is an interdisciplinary field that focuses on extracting knowledge and insights from structured and unstructured data. It combines statistics, mathematics, computer science, and domain expertise to solve complex problems. Data Science, however, uses predictive and prescriptive solutions.
52 
NYU Center for Data Science
DECEMBER 12, 2024
This year, CDS faculty, researchers, and students will present research spanning an extraordinary range of topics, from theoretical advances in optimization and neural networks to practical applications in computer vision and natural language processing.
ODSC - Open Data Science
FEBRUARY 17, 2023
Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. Computer science, math, statistics, programming, and software development are all skills required in NLP projects.
111 
AWS Machine Learning Blog
NOVEMBER 15, 2024
It provides a common framework for assessing the performance of natural language processing (NLP)-based retrieval models, making it straightforward to compare different approaches. Yang holds a Bachelor’s and Master’s degree in Computer Science from Texas A&M University.
110 
Dataconomy
MARCH 14, 2023
In recent years, natural language processing and conversational AI have gained significant attention as technologies that are transforming the way we interact with machines and each other. This necessitates a flexible, efficient, and generalizable learning algorithm. What is natural language processing (NLP)?
Towards AI
JANUARY 6, 2025
Professional certificate for computer science for AI by HARVARD UNIVERSITY Professional certificate for computer science for AI is a 5-month AI course that is inclusive of self-paced videos for participants; who are beginners or possess intermediate-level understanding of artificial intelligence.
Dataconomy
MARCH 23, 2023
Artificial intelligence is a branch of computer science that involves the development of intelligent machines that can perform tasks that typically require human intelligence. AI technologies include machine learning, natural language processing, computer vision, and robotics, among others.
Dataconomy
APRIL 12, 2023
By incorporating insights from cognitive science, AI is becoming more advanced and capable, with the potential to transform many aspects of our lives. Artificial intelligence, or AI, is a field of computer science and engineering that focuses on creating machines and systems that can perform tasks that typically require human intelligence.
ODSC - Open Data Science
DECEMBER 19, 2023
Data scientists with a PhD or a master’s degree in computer science or a related field can earn more than $150,000 per year. They use their knowledge of machine learning algorithms, programming languages, and data science tools to build models that can be used to automate tasks and make predictions.
Dataconomy
MARCH 13, 2023
With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. However, the process of creating AI can seem daunting to those who are unfamiliar with the technicalities involved. Train and evaluate the AI models for accuracy and efficiency.
Data Science Dojo
JUNE 4, 2024
Some common topics discussed and covered in AI books include search algorithms, machine learning, natural language processing, and computer vision – the building blocks of intelligent systems. They cover multiple aspects of a topic in-depth, providing a detailed repository of information for readers.
195 
Dataconomy
APRIL 3, 2023
Artificial intelligence, commonly referred to as AI , is the field of computer science that focuses on the development of intelligent machines that can perform tasks that would typically require human intervention. Unsupervised learning: In unsupervised learning, the algorithm is trained on unlabeled data.
Dataconomy
APRIL 3, 2023
Artificial intelligence, commonly referred to as AI , is the field of computer science that focuses on the development of intelligent machines that can perform tasks that would typically require human intervention. Unsupervised learning: In unsupervised learning, the algorithm is trained on unlabeled data.
Towards AI
AUGUST 16, 2023
AI engineering is the discipline focused on developing tools, systems, and processes to enable the application of artificial intelligence in real-world contexts, which combines the principles of systems engineering, software engineering, and computer science to create AI systems.
98 
NYU Center for Data Science
DECEMBER 12, 2023
In an era where algorithms determine everything from creditworthiness to carceral sentencing, the imperative for responsible innovation has never been more urgent. Andrew Bell and Lucius Bynum: Challenging Algorithmic Boundaries Andrew Bell’s exploration of algorithmic fairness sets a foundation for the responsible AI dialogue.
98 
IBM Journey to AI blog
DECEMBER 20, 2023
Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. What is machine learning?
ML @ CMU
FEBRUARY 24, 2023
This formulation also allows us to employ off-the-shelf RL algorithms (e.g., Discrete prompt optimization thus amounts to learning a small number of policy parameters which we set as an MLP layer inserted into a frozen compact model such as distilGPT-2. We describe the specific formulations in Section §2.1-2.3 of our paper.
Dataconomy
MARCH 23, 2023
Artificial intelligence is a branch of computer science that involves the development of intelligent machines that can perform tasks that typically require human intelligence. AI technologies include machine learning, natural language processing, computer vision, and robotics, among others.
AWS Machine Learning Blog
OCTOBER 6, 2023
Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. To simplify, you can build a regression algorithm using a user’s previous ratings across different categories to infer their overall preferences.
139 
AWS Machine Learning Blog
JANUARY 13, 2023
Because ML algorithms are often not adequate in protecting the privacy of patient-level data, there is a growing interest among HCLS partners and customers to use privacy-preserving mechanisms and infrastructure for managing and analyzing large-scale, distributed, and sensitive data. [1].
100 
Pickl AI
APRIL 25, 2023
There are various Machine Learning algorithms including regression and classification algorithms. Consequently, ML algorithms can be further divided into two categories, supervised and unsupervised. Supervised algorithms require you to train datasets for both the input data and the desired output. What is NLP?
AWS Machine Learning Blog
FEBRUARY 25, 2025
Model invocation We use Anthropics Claude 3 Sonnet model for the natural language processing task. This LLM model has a context window of 200,000 tokens, enabling it to manage different languages and retrieve highly accurate answers. temperature This parameter controls the randomness of the language models output.
78 
AWS Machine Learning Blog
MAY 31, 2024
trillion token dataset and supports multiple languages. The Falcon 2 11B model is available on SageMaker JumpStart, a machine learning (ML) hub that provides access to built-in algorithms, FMs, and pre-built ML solutions that you can deploy quickly and get started with ML faster. Falcon 2 11B is a trained dense decoder model on a 5.5
122 
AWS Machine Learning Blog
NOVEMBER 9, 2023
This retrieval can happen using different algorithms. Her research interests lie in Natural Language Processing, AI4Code and generative AI. Xiaofei has been serving as the science manager for several services including Kendra, Contact Lens, and most recently CodeWhisperer and CodeGuru Security.
116 Dataconomy
MAY 2, 2023
They design, develop, and deploy the machine learning algorithms that power everything from self-driving cars to personalized recommendations. They are the driving force behind the artificial intelligence revolution, creating new opportunities and possibilities that were once the stuff of science fiction. They build the future.
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