Data Science Dojo

SEPTEMBER 11, 2023

From virtual assistants like Siri and Alexa to personalized recommendations on streaming platforms, chatbots, and language translation services, language models surely are the engines that power it all.

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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. Moreover, the model training process is capable of adapting to new languages and data effectively.

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Dataconomy

APRIL 3, 2023

Understanding the basic components of artificial intelligence is crucial for developing and implementing AI technologies. 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.

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Dataconomy

APRIL 3, 2023

Understanding the basic components of artificial intelligence is crucial for developing and implementing AI technologies. 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.

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Towards AI

JANUARY 30, 2024

Author(s): Abhinav Kimothi Originally published on Towards AI. Being new to the world of Generative AI, one can feel a little overwhelmed by the jargon. Designed to be general-purpose, providing a foundation for various AI applications. Instead of formalised code syntax, you provide natural language inputs to the models.

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Becoming Human

MAY 9, 2024

Artificial intelligence, machine learning, natural language processing, and other related technologies are paving the way for a smarter “everything.” As a result, we can automate manual processes, improve risk management, comply with regulations, and maintain data consistency.

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Towards AI

MARCH 4, 2023

Last Updated on March 4, 2023 by Editorial Team Author(s): Harshit Sharma Originally published on Towards AI. Fully-Supervised Learning (Non-Neural Network) — powered by — Feature Engineering Supervised learning required input-output examples to train the model. Join thousands of data leaders on the AI newsletter.

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Dataconomy

MAY 25, 2023

By harnessing the power of AI in IoT, we can create intelligent ecosystems where devices seamlessly communicate, collaborate, and make intelligent choices to improve our lives. Let’s explore the fascinating intersection of these two technologies and understand how AI enhances the functionalities of IoT.

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Women in Big Data

DECEMBER 13, 2023

The Bay Area Chapter of Women in Big Data (WiBD) hosted its second successful episode on the NLP (Natural Language Processing), Tools, Technologies and Career opportunities. We are hearing about NLP, LLMs, ChatGPT and Generative AI a lot ! Computational Linguistics is rule based modeling of natural languages.

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Mlearning.ai

AUGUST 4, 2023

Fine-tuning large language models (LLMs) has become a powerful technique for achieving impressive performance in various natural language processing tasks. Additionally, few-shot learning requires maintaining a large context window, which can be resource-intensive and impractical for memory-constrained environments.

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ODSC - Open Data Science

AUGUST 29, 2023

Since OpenAI’s ChatGPT kicked down the door and brought large language models into the public imagination, being able to fully utilize these AI models has quickly become a much sought-after skill. With that said, companies are now realizing that to bring out the full potential of AI, prompt engineering is a must.

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Towards AI

FEBRUARY 20, 2024

Last Updated on February 20, 2024 by Editorial Team Author(s): Vaishnavi Seetharama Originally published on Towards AI. Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms.

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Becoming Human

MAY 11, 2023

Artificial intelligence (AI) has come a long way in recent years, and one of the most exciting developments in this field is the rise of language models like ChatGPT. In this article, we will explore these factors in more detail, and examine how they have contributed to the rise of ChatGPT and other language models.

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ODSC - Open Data Science

NOVEMBER 8, 2023

Generative AI is a new field. Over the past year, new terms, developments, algorithms, tools, and frameworks have emerged to help data scientists and those working with AI develop whatever they desire. One common approach is to use supervised learning. You can even fine-tune prompts to get exactly what you want.

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IBM Journey to AI blog

JUNE 14, 2023

Sometimes the problem with artificial intelligence (AI) and automation is that they are too labor intensive. Traditional AI tools, especially deep learning-based ones, require huge amounts of effort to use. And then you need highly specialized, expensive and difficult to find skills to work the magic of training an AI model.

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ODSC - Open Data Science

APRIL 26, 2023

AI is quickly scaling and being adopted by multiple industries at a rapid pace, none more than healthcare and biopharma. Not only is AI helping these groups that specialize in healthcare and biopharma with optimizing costs, but it is also opening the doors to new discoveries that can potentially rock the foundations of healthcare.

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ODSC - Open Data Science

OCTOBER 15, 2023

Here is the second half of our two-part series of companies changing the face of AI. AI is quickly scaling through dozens of industries as companies, non-profits, and governments are discovering the power of artificial intelligence. However, there are some critical differences between the two companies.

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Dataconomy

MARCH 13, 2023

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. How to create an artificial intelligence?

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Smart Data Collective

JUNE 4, 2021

Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. Learning the various categories of machine learning, associated algorithms, and their performance parameters is the first step of machine learning. In supervised learning, a variable is predicted.

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Pickl AI

AUGUST 1, 2023

As technology continues to impact how machines operate, Machine Learning has emerged as a powerful tool enabling computers to learn and improve from experience without explicit programming. In this blog, we will delve into the fundamental concepts of data model for Machine Learning, exploring their types.

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AWS Machine Learning Blog

NOVEMBER 27, 2023

Generative artificial intelligence ( generative AI ) models have demonstrated impressive capabilities in generating high-quality text, images, and other content. While this data holds valuable insights, its unstructured nature makes it difficult for AI algorithms to interpret and learn from it. read HTML).

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ODSC - Open Data Science

SEPTEMBER 19, 2023

They are the detectives and accuracy hunters of the AI world. Depending on the position, and company, it can require a strong understanding of natural language processing, computer science, linguistics, and software engineering. Learn more about our upcoming events here. Interested in attending an ODSC event?

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Mlearning.ai

APRIL 21, 2023

Text annotation Text annotation is the process of adding structured information to unstructured text data in order to make it more understandable and useful for downstream applications. The resulting annotated text data can then be used to train and improve the accuracy of LLM models for specific natural language processing tasks.

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Pickl AI

AUGUST 7, 2023

Data Labelling is the process of adding meaning to different datasets ensuring that it can be used properly to train a Machine Learning model. Labeled data in Machine Learning is typically used in the case of Supervised Learning where the labeled data is input to a model. How does Data Labelling Work?

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Mlearning.ai

JULY 11, 2023

12 Best Deep Learning Courses on Coursera Step 2: Understand Machine Learning Basics Before diving into deep learning, grasp the fundamentals of machine learning. Learn how to fine-tune model parameters effectively. Step 6: Apply Deep Learning to Specific Domains Deep learning is used in many areas.

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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. That is, is giving supervision to adjust via.

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Heartbeat

OCTOBER 11, 2023

This process is known as machine learning or deep learning. Two of the most well-known subfields of AI are machine learning and deep learning. Supervised, unsupervised, and reinforcement learning : Machine learning can be categorized into different types based on the learning approach.

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Dataconomy

MARCH 27, 2023

RPA is often considered a form of artificial intelligence, but it is not a complete AI solution. AI, on the other hand, can learn from data and adapt to new situations without human intervention. Unsupervised learning:  This involves using unlabeled data to identify patterns and relationships within the data.

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Hacker News

MARCH 25, 2022

If you want to ride the next big wave in AI, grab a transformer. A transformer model is a neural network that learns context and thus meaning by tracking relationships in sequential data like the words in this sentence. They’re driving a wave of advances in machine learning some have dubbed transformer AI.

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Snorkel AI

MARCH 24, 2023

Snorkel AI researchers continue to push the frontier of machine learning, as demonstrated by the 18 research papers recently added to our website. This batch of research papers, all published in 2022, present new developments in weak supervision and foundation models. On the Opportunities and Risks of Foundation Models R.

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Snorkel AI

MARCH 24, 2023

Snorkel AI researchers continue to push the frontier of machine learning, as demonstrated by the 18 research papers recently added to our website. This batch of research papers, all published in 2022, present new developments in weak supervision and foundation models. On the Opportunities and Risks of Foundation Models R.

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AWS Machine Learning Blog

AUGUST 16, 2023

Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. One way to overcome this challenge is through self-supervised learning (SSL). Jeremy Anderson is a Director & Data Scientist at Travelers on the AI & Automation Accelerator team.

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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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IBM Journey to AI blog

JULY 6, 2023

What is machine learning? Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with. Machine learning can then “learn” from the data to create insights that improve performance or inform predictions.

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PyImageSearch

MARCH 30, 2023

What is Machine Learning A Closer Look at Machine Learning Machine learning (ML) revolves around creating algorithms and related systems that learn behavior strategies in specific environments using instructions and training data sets.

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Dataconomy

MARCH 27, 2023

RPA is often considered a form of artificial intelligence, but it is not a complete AI solution. AI, on the other hand, can learn from data and adapt to new situations without human intervention. Unsupervised learning:  This involves using unlabeled data to identify patterns and relationships within the data.

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Pickl AI

AUGUST 1, 2023

Text mining is also known as text analytics or Natural Language Processing (NLP). It is the process of deriving valuable patterns, trends, and insights from unstructured textual data. Support Vector Machines (SVM): A supervised learning algorithm used for text classification and document clustering.

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