Towards AI

JULY 23, 2023

Semi-Supervised Sequence Learning As we all know, supervised learning has a drawback, as it requires a huge labeled dataset to train. Generating Wikipedia By Summarizing Long Sequences This work was published by Peter J Liu at Google in 2019. But, the question is, how did all these concepts come together?

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AWS Machine Learning Blog

AUGUST 7, 2023

As opposed to training a model from scratch with task-specific data, which is the usual case for classical supervised learning, LLMs are pre-trained to extract general knowledge from a broad text dataset before being adapted to specific tasks or domains with a much smaller dataset (typically on the order of hundreds of samples).

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Snorkel AI

MARCH 1, 2023

Foundation Models (FMs), such as GPT-3 and Stable Diffusion, mark the beginning of a new era in machine learning and artificial intelligence. Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning?

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Mlearning.ai

AUGUST 20, 2023

Photo by Bruno Nascimento on Unsplash Introduction Data is the lifeblood of Machine Learning Models. Before we feed data into a learning algorithm, we need to make sure that we pre-process the data. Many Machine Learning algorithms don’t work with missing data. 2019) Data Science with Python. England, A.

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Mlearning.ai

APRIL 16, 2023

It may seem simple linear regression is neglected in the machine learning world of today. In this tutorial, you will learn about the concepts behind simple linear regression. There are various types of regressions used in data science and machine learning. 2021) Machine Learning for Beginners.

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Mlearning.ai

SEPTEMBER 24, 2023

This is a technique for evaluating Machine Learning models. 2019) Data Science with Python. 2019) Applied Supervised Learning with Python. Then, GridSearchCV evaluates the model performance for each combination of the hyperparameter values. The result is the optimal combination of values from this set.

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Hacker News

FEBRUARY 14, 2023

It’s better than the top-word (zero temperature) case, but still at best a bit weird: This was done with the simplest GPT-2 model (from 2019). And—as we’ll discuss later—these weights are normally determined by “training” the neural net using machine learning from examples of the outputs we want.)

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Chatbots Life

MAY 12, 2023

A solution to this problem presented by OpeanAI is reinforcement learning. Reinforcement learning is a machine learning training method based on rewarding desired behaviours and punishing undesired ones. Trained with reinforcement learning to generate completions that are more desired by the user.

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Google Research AI blog

JANUARY 18, 2023

I will begin with a discussion of language, computer vision, multi-modal models, and generative machine learning models. Language Models The progress on larger and more powerful language models has been one of the most exciting areas of machine learning (ML) research over the last decade. Left: From I. Goodfellow, et al.

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Snorkel AI

MAY 25, 2023

Data scientists and researchers train LLMs on enormous amounts of unstructured data through self-supervised learning. The model then predicts the missing words (see “what is self-supervised learning?” OpenAI’s GPT-2, finalized in 2019 at 1.5 billion parameters, raised eyebrows by producing convincing prose.

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Snorkel AI

MAY 25, 2023

Data scientists and researchers train LLMs on enormous amounts of unstructured data through self-supervised learning. The model then predicts the missing words (see “what is self-supervised learning?” OpenAI’s GPT-2, finalized in 2019 at 1.5 billion parameters, raised eyebrows by producing convincing prose.

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Natural Language Processing Python Machine Learning Machine Learning 52

DrivenData Labs

FEBRUARY 3, 2025

Recently, I became interested in machine learning, so I was enrolled in the Yandex School of Data Analysis and Computer Science Center. Machine learning is my passion and I often participate in competitions. The semi-supervised learning was repeated using the gemma2-9b model as the soft labeling model.

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Kaggle

JULY 29, 2020

Photo by Clay Banks on Unsplash Let’s learn about David! link] David Mezzetti is the founder of NeuML, a data analytics and machine learning company that develops innovative products backed by machine learning. In August 2019, Data Works was acquired and Dave worked to ensure a successful transition.

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