Data Science Dojo

APRIL 25, 2025

Agentic AI is a type of artificial intelligence (AI) that does not just follow rules but acts like an intelligent agent. You can also use supervised learning if you already have labeled data to teach the agent. Ready to explore more? Lets dive in. What is Agentic AI? Agentic AI is shaping the future.

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Data Science Dojo

MAY 27, 2024

In the recent discussion and advancements surrounding artificial intelligence, there’s a notable dialogue between discriminative and generative AI approaches. By spotting features in the data, discriminative models help classify the input into specific groups without looking deep into how the data is spread out.

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Data Science Blog

FEBRUARY 23, 2023

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves.

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Data Science Dojo

SEPTEMBER 5, 2023

This unveiling marks a significant progression for Microsoft, a company that has made substantial investments in artificial intelligence (AI), with a particular emphasis on OpenAI, the pioneering creators behind renowned models like DALL-E, ChatGPT, and the formidable GPT language model.

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Data Science Dojo

AUGUST 19, 2024

Industry Adoption: Widespread Implementation: AI and data science are being adopted across various industries, including healthcare, finance, retail, and manufacturing, driving increased demand for skilled professionals. The model learns to map input features to output labels.

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Dataconomy

MARCH 13, 2023

How to create an artificial intelligence? The creation of artificial intelligence (AI) has long been a dream of scientists, engineers, and innovators. With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless.

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Pickl AI

SEPTEMBER 23, 2024

Summary: The blog explores the synergy between Artificial Intelligence (AI) and Data Science, highlighting their complementary roles in Data Analysis and intelligent decision-making. This article explores how AI and Data Science complement each other, highlighting their combined impact and potential.

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NYU Center for Data Science

NOVEMBER 15, 2023

Pinheiro, Joshua Rackers, Joseph Kleinhenz, Michael Maser, *Omar Mahmood (PhD alumnus), Andrew Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi “A Logic for Expressing Log-Precision Transformers” : *William Merrill (PhD student), Ashish Sabharwal “A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks” : Vignesh Kothapalli, Tom (..)

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Dataconomy

APRIL 27, 2022

Contrary to popular belief, the history of machine learning, which enables machines to learn tasks for which they are not specifically programmed, and train themselves in unfamiliar environments, goes back to 17th century. Machine learning is a powerful tool for implementing artificial intelligence technologies.

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Data Science Dojo

DECEMBER 8, 2023

Counting Shots, Making Strides: Zero, One and Few-Shot Learning Unleashed In the dynamic field of artificial intelligence, traditional machine learning, reliant on extensive labeled datasets, has given way to transformative learning paradigms. Welcome to the frontier of machine learning innovation!

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Dataconomy

SEPTEMBER 13, 2023

Data forms the foundation of the modern customer experience. As businesses gather increasingly deep insights into their customers, artificial intelligence (AI) emerges as a powerful ally to turn this data into actionable strategies. Accurate data annotation is critical to Tesla achieving full self-driving.

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Pickl AI

APRIL 3, 2023

Therefore, Supervised Learning vs Unsupervised Learning is part of Machine Learning. Let’s learn more about supervised and Unsupervised Learning and evaluate their differences. What is Supervised Learning? What is Unsupervised Learning?

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How to Learn Machine Learning

MAY 2, 2025

Best Practices for Azure Machine Learning Projects To get the most out of Azure Machine Learning, consider these best practices: Data Management Use Azure Data Stores : Connect to various data sources including Azure Blob Storage, Azure Data Lake, and Azure SQL Database for efficient data access.

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Smart Data Collective

JUNE 7, 2019

Machine learning is playing a very important role in improving the functionality of task management applications. In January, Towards Data Science published an article on this very topic. “In They will be able to take better advantage of the functionality if they have a deeper understanding of the data science behind it.

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ODSC - Open Data Science

MARCH 7, 2025

In the fast-moving world of AI and data science, high-quality financial datasets are essential for building effective models. Whether its algorithmic trading , risk assessment, fraud detection , credit scoring, or market analysis, the accuracy and depth of financial data can make or break an AI-driven solution.

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Towards AI

FEBRUARY 13, 2024

Louis-François Bouchard in What is Artificial Intelligence Introduction to self-supervised learning·4 min read·May 27, 2020 80 … Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter. Author(s): Louis-François Bouchard Originally published on Towards AI.

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IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

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Becoming Human

MAY 15, 2023

Data Science is a popular as well as vast field; till date, there are a lot of opportunities in this field, and most people, whether they are working professionals or students, everyone want a transition in data science because of its scope. How much to learn? What to do next?

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Towards AI

JANUARY 29, 2025

Whether youre a beginner or an expert, this comprehensive guide will take you through Scikit-learn from A to Z, unlocking its potential to solve real-world problems. Scikit-learn is an open-source machine learning library built on Python. regression, classification)Unsupervised Learning (e.g.,

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Mlearning.ai

JANUARY 31, 2023

Unlock the full potential of supervised learning with advanced techniques such as Regularization, Explainability, and more Continue reading on MLearning.ai »

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

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NYU Center for Data Science

MAY 31, 2023

CDS Assistant Professor/Faculty Fellow Jacopo Cirrone discusses his work harnessing data science in medical image analysis CDS Assistant Professor/Faculty Fellow, Dr. Jacopo Cirrone Medical image analysis has significantly benefited in recent years from machine learning-based modeling tools.

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Pickl AI

OCTOBER 20, 2024

Summary: Learning Artificial Intelligence involves mastering Python programming, understanding Machine Learning principles, and engaging in practical projects. Introduction Artificial Intelligence (AI) is transforming industries worldwide, with applications in healthcare, finance, and technology.

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Pickl AI

JANUARY 12, 2023

Due to the growing application of Data Science in different industries, companies are now looking forward to hiring individuals and training their employees on newer technologies that can eventually help the organization attain its goals. Best Data Science courses for working professionals 1.

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ODSC - Open Data Science

FEBRUARY 10, 2023

What worked best was an algorithm that combined two sub-fields of machine learning, supervised learning, and unsupervised learning. Originally posted on OpenDataScience.com Read more data science articles on OpenDataScience.com , including tutorials and guides from beginner to advanced levels!

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Pickl AI

SEPTEMBER 12, 2024

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

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IBM Journey to AI blog

DECEMBER 20, 2023

What is machine learning? 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. Here, we’ll discuss the five major types and their applications. temperature, salary).

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Pickl AI

DECEMBER 4, 2024

Summary: Data Science appears challenging due to its complexity, encompassing statistics, programming, and domain knowledge. However, aspiring data scientists can overcome obstacles through continuous learning, hands-on practice, and mentorship. However, many aspiring professionals wonder: Is Data Science hard?

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Pickl AI

MAY 31, 2023

With the expanding field of Data Science, the need for efficient and skilled professionals is increasing. Its efficacy may allow kids from a young age to learn Python and explore the field of Data Science. Its efficacy may allow kids from a young age to learn Python and explore the field of Data Science.

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Towards AI

AUGUST 29, 2023

Introducing the backbone of Reinforcement Learning — The Markov Decision Process This member-only story is on us. Image by Ricardo Gomez Angel on Unsplash In most of my previous articles, I have mostly discussed Supervised Learning, with some sprinkling of elements of Unsupervised Learning.

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IBM Journey to AI blog

DECEMBER 19, 2023

Anomalies are not inherently bad, but being aware of them, and having data to put them in context, is integral to understanding and protecting your business. The challenge for IT departments working in data science is making sense of expanding and ever-changing data points.

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Data Science Dojo

JULY 31, 2024

We will also look into some of the leading multimodal LLMs in the market and their role in dealing with versatile data inputs. In the context of Artificial Intelligence (AI), a modality refers to a specific type or form of data that can be processed and understood by AI models. What is Multimodal AI?

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AWS Machine Learning Blog

SEPTEMBER 10, 2024

In this post, we detail our collaboration in creating two proof of concept (PoC) exercises around multi-modal machine learning for survival analysis and cancer sub-typing, using genomic (gene expression, mutation and copy number variant data) and imaging (histopathology slides) data.

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NYU Center for Data Science

DECEMBER 12, 2024

NeurIPS has long been one of the most influential venues in machine learning and artificial intelligence, known for featuring work that shapes the future of thesefields. The breadth and depth of these papers illustrate CDS commitment to pushing forward the boundaries of data science through rigorous, innovative research.

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Dataconomy

MARCH 27, 2023

Robotic process automation vs machine learning is a common debate in the world of automation and artificial intelligence. The differences between robotic process automation vs machine learning lie in their functionality, purpose, and the level of human intervention required Is RPA artificial intelligence?

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Data Science Dojo

JULY 2, 2024

It is a step ahead within the realm of artificial intelligence (AI). Since adaptive AI has emerged as a new and advanced branch of artificial intelligence, it is important to understand the basic qualities that make it stand out. It has led to enhanced use of AI in various real-world applications.

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Data Science Dojo

SEPTEMBER 11, 2023

And language models as we talk about, lie at the center of NLP, they are the heart of NLP and are designed to predict the likelihood of a word or a phrase given the context of a sentence or a series of words.

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