Data Science Blog

MARCH 26, 2023

This is the sixth article of the series My elaborate study notes on reinforcement learning. In this article series “the book by Barto and Sutton” means “Reinforcement Learning: An Introduction second edition” This book is said to be almost mandatory for those who seriously learn Reinforcement Learning (RL).

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Towards AI

JANUARY 28, 2024

Image by [link] Machine learning, data mining, deep learning, and advanced optimization algorithms all rely heavily on linear algebra. Linear algebra is widely used in almost all machine learning algorithms. For example, Gaussian elimination aids in the solution of normal equations derived from the least squares method.

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Dataconomy

MAY 4, 2023

Machine learning applications in healthcare are rapidly advancing, transforming the way medical professionals diagnose, treat, and prevent diseases. In this rapidly evolving field, machine learning is poised to drive significant advancements in healthcare, improving patient outcomes and enhancing the overall healthcare experience.

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Heartbeat

JANUARY 29, 2024

Photo by Brett Jordan on Unsplash In the ever-evolving landscape of artificial intelligence and machine learning, researchers and practitioners continuously seek to elevate the capabilities of intelligent systems. Among the myriad breakthroughs in this field, Meta-Learning is pushing the boundaries of machine learning.

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Snorkel AI

APRIL 30, 2024

For example, in classifying water birds versus land birds, if the pre-training dataset often shows water birds in front of water and land birds on land, the model may mistakenly use the background as the basis for its prediction. This process, while effective, requires substantial human and computational resources. A promising start.

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Heartbeat

JULY 5, 2023

In this article, you will learn how to use RL and NLP to create an entire chatbot system. What is Reinforcement? Reinforcement learning is a subfield of machine learning (ML) that teaches an agent to learns how to act in a particular setting in order to maximize the reward signal there. Why is NLP Required?

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Snorkel AI

APRIL 30, 2024

For example, in classifying water birds versus land birds, if the pre-training dataset often shows water birds in front of water and land birds on land, the model may mistakenly use the background as the basis for its prediction. This process, while effective, requires substantial human and computational resources. A promising start.

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AWS Machine Learning Blog

SEPTEMBER 22, 2023

Reinforcement Learning from Human Feedback (RLHF) is recognized as the industry standard technique for ensuring large language models (LLMs) produce content that is truthful, harmless, and helpful. Reward models and reinforcement learning are applied iteratively with human-in-the-loop feedback.

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Google Research AI blog

APRIL 30, 2023

Posted by Catherine Armato, Program Manager, Google The Eleventh International Conference on Learning Representations (ICLR 2023) is being held this week as a hybrid event in Kigali, Rwanda. We are proud to be a Diamond Sponsor of ICLR 2023, a premier conference on deep learning, where Google researchers contribute at all levels.

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Heartbeat

MAY 30, 2023

Photo by Othmar Vigl on Pexels Introduction Generative Adversarial Networks (GANs) and Deep Reinforcement Learning (DRL) are two popular and continuously developing artificial intelligence subfields that have gotten a lot of interest and research in recent years. What is Deep Reinforcement Learning (DRL)?

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IBM Journey to AI blog

APRIL 11, 2023

Today, I want to share some examples that highlight IBM’s 2022 progress in the area of social impact. That is why we take our commitment to providing career training, learning opportunities and career growth very seriously. In 2022, we increased the hours of learning per employee.

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Dataconomy

MAY 25, 2023

Simultaneously, artificial intelligence has revolutionized the way machines learn, reason, and make decisions. On the other hand, artificial intelligence is the simulation of human intelligence in machines that are programmed to think and learn like humans.

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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. What is Machine Learning? Machine learning algorithms can make predictions or classifications based on input data.

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ODSC - Open Data Science

SEPTEMBER 21, 2023

The majority of us who work in machine learning, analytics, and related disciplines do so for organizations with a variety of different structures and motives. In pretty much all of these cases, we do not do this work in a vacuum and not with an infinite budget of time or resources.

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IBM Journey to AI blog

DECEMBER 4, 2023

Business leaders overestimate the resources required to pursue AI, often unaware of the available technology and training. We also provide the same contractual intellectual property protections  for IBM-developed AI models as we do for all our products, reinforcing trust in businesses’ AI journeys.

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Hacker News

AUGUST 3, 2023

One such method, Reinforcement Learning from Human Feedback (RLHF) , is currently leading the charge. The first step is to create a dataset of examples reflecting human preferences. Once the reward model is ready, it can be used to fine-tune the base model via Reinforcement Learning.

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Flipboard

JANUARY 3, 2024

We can better prioritize infrastructure, prioritize resources, prioritize tooling, upskilling, training and so forth.” We have other efforts that we are just starting with the Department of Energy — for example, to accelerate permitting processes. “It makes sense to bring everybody together in a virtual research hub.

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ODSC - Open Data Science

JULY 26, 2023

As a senior data scientist, I often encounter aspiring data scientists eager to learn about machine learning (ML). It’s a fascinating field that can seem daunting at first, but I assure you, with the right mindset and resources, anyone can master it. What is Machine Learning? spam vs. non-spam emails) and regression (e.g.,

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Heartbeat

FEBRUARY 27, 2023

Photo by Markus Spiske on Unsplash Deep learning has grown in importance as a focus of artificial intelligence research and development in recent years. Deep Reinforcement Learning (DRL) and Generative Adversarial Networks (GANs) are two promising deep learning trends. A diagram of how a GAN works.

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Becoming Human

JUNE 5, 2023

However, traditional machine learning models have struggled to keep pace with the dynamic nature of our rapidly evolving world, hindering their effectiveness in handling the influx of data generated by the Internet of Things (IoT) and autonomous vehicles. Fortunately, the emergence of adaptive AI is changing the game.

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Pickl AI

NOVEMBER 3, 2023

Learning Data Science from YouTube is a flexible, cost-effective, and accessible way to gain knowledge and skills in this rapidly growing field. It empowers individuals to take control of their learning journey and stay updated with the latest advancements, making it a beneficial choice for both beginners and experienced professionals.

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ODSC - Open Data Science

JANUARY 10, 2024

Learn more about our first-announced sessions coming to the event this April 23rd-25th below. How do we figure out what is causal and what isn’t, with a brief introduction to methods of structure learning and causal discovery? Get practical experience and return to work ready to start implementing these concepts in your daily work.

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AWS Machine Learning Blog

MAY 9, 2024

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. According to a McKinsey study , across the financial services industry (FSI), generative AI is projected to deliver over $400 billion (5%) of industry revenue in productivity benefits.

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Dataconomy

JULY 27, 2023

As we continue to rely more on AI-powered technologies, it’s mandatory to address the issue of bias in machine learning. Unfortunately, this bias can easily seep into machine learning algorithms, creating significant challenges when it comes to developing fair, transparent, and impartial decision-making procedures.

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Data Science Dojo

APRIL 18, 2024

The answer lies in large language models (LLMs) – machine-learning models that empower machines to learn, understand, and interact using human language. As LLMs continue to learn and grow, they’re poised to be a game-changer in the world of language and artificial intelligence. Read more about it here.

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Google Research AI blog

FEBRUARY 14, 2023

An undercurrent this past year has been the exploration of how large, generalist models, like PaLM , can work alongside other approaches to surface capabilities allowing robots to learn from a breadth of human knowledge and allowing people to engage with robots more naturally.

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AWS Machine Learning Blog

OCTOBER 5, 2023

For example, to use the RedPajama dataset, use the following command: wget [link] python nemo/scripts/nlp_language_modeling/preprocess_data_for_megatron.py For the complete example code and scripts we mentioned, refer to the Llama 7B tutorial and NeMo code in the Neuron SDK to walk through more detailed steps.

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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. By automating routine tasks, RPA helps organizations to improve operational efficiency, reduce costs, and free up human resources to focus on more complex tasks.

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Heartbeat

NOVEMBER 27, 2023

Deep learning automates and improves medical picture analysis. Convolutional neural networks (CNNs) can learn complicated patterns and features from enormous datasets, emulating the human visual system. Convolutional Neural Networks (CNNs) Deep learning in medical image analysis relies on CNNs.

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Heartbeat

MARCH 14, 2023

photo from Data Science Central Industrial automation, security and surveillance, and service robots are just a few examples of fields that might benefit from robotics’ ability to identify and track objects. Scene Understanding The act of learning about a scene and the things in it is called scene understanding.

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PyImageSearch

JANUARY 30, 2023

In emerging markets, AI has the potential to provide affordable post-secondary education, make learning exciting and fun, and make the content personalized to individual students’ needs. This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector.

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Dataconomy

JUNE 13, 2023

From optimizing resource allocation to mitigating risks, from uncovering untapped market opportunities to delivering personalized customer experiences, decision intelligence is a guiding compass that empowers businesses to navigate the complexities of today’s competitive world.

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Dataconomy

MAY 16, 2023

Machine learning engineer vs data scientist: two distinct roles with overlapping expertise, each essential in unlocking the power of data-driven insights. As businesses strive to stay competitive and make data-driven decisions, the roles of machine learning engineers and data scientists have gained prominence.

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Pickl AI

MAY 29, 2023

How to Learn Python Step by Step The best way to learn Python is to begin with enrolment for the best Python programming course provider. Also, there are several benefits of learning Python. An excellent example is Pickl.AI, offering the best online Python course with a certificate.

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Smart Data Collective

AUGUST 15, 2022

On the other hand, limited memory AI consists of machine learning models that can extract knowledge from previously learned facts, information, events, or stored data. Through the combination of AI and machine learning that gathers and analyzes behavioral, historical, and social data, brands can now better understand their customers.

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Becoming Human

MAY 15, 2023

LLMs are designed to process vast amounts of text data and use advanced neural network architectures to learn the patterns and relationships between words, phrases, and concepts in natural language. ChatGPT , a chatbot developed by the OpenAI team, is an example of an LLM. You can even try this out on the OpenAI website to get a feel.

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Pickl AI

SEPTEMBER 21, 2023

The Role of Pre-Training and Fine-Tuning Language model optimization is a complex process that typically involves two main phases: Pre-training In the pre-training phase, a model is exposed to a vast corpus of text, learning grammar, facts, and reasoning abilities. These include data augmentation, active learning, and hyperparameter tuning.

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