AWS Machine Learning Blog

MAY 2, 2023

With the ability to solve various problems such as classification and regression, XGBoost has become a popular option that also falls into the category of tree-based models. These models have long been used for solving problems such as classification or regression. threshold – This is a score threshold for determining classification.

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Mlearning.ai

DECEMBER 19, 2023

Modifying Microsoft Phi 2 LLM for Sequence Classification Task. Transformer-Decoder models have shown to be just as good as Transformer-Encoder models for classification tasks (checkout winning solutions in the kaggle competition: predict the LLM where most winning solutions finetuned Llama/Mistral/Zephyr models for classification).

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AWS Machine Learning Blog

APRIL 8, 2024

This version offers support for new models (including Mixture of Experts), performance and usability improvements across inference backends, as well as new generation details for increased control and prediction explainability (such as reason for generation completion and token level log probabilities).

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Shreyansh Singh

MAY 16, 2021

It outperforms BERT in 20 NLP tasks like question answering, natural language inference, sentiment analysis and document ranking. XLNet integrates the novelties from Transformer-XL like recurrence mechanism and relative encoding scheme (explained later as well). Performance on text classification task. and SQuADv2.0

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AWS Machine Learning Blog

JANUARY 17, 2024

Llama 2 is an auto-regressive generative text language model that uses an optimized transformer architecture. As a publicly available model, Llama 2 is designed for many NLP tasks such as text classification, sentiment analysis, language translation, language modeling, text generation, and dialogue systems.

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The MLOps Blog

FEBRUARY 27, 2023

Also, science projects around technologies like predictive modeling, computer vision, NLP, and several profiles like commercial proof of concepts and competitions workshops. Michal, to warm you up for all this question-answering, how would you explain to us managing computer vision projects in one minute? This is a much harder thing.

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AWS Machine Learning Blog

SEPTEMBER 6, 2023

What is Llama 2 Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. After it’s fine-tuned on the domain-specific dataset, the model is expected to generate domain-specific text and solve various NLP tasks in that specific domain with few-shot prompting.

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Mlearning.ai

MAY 23, 2023

DOE: stands for the design of experiments, which represents the task design aiming to describe and explain information variation under hypothesized conditions to reflect variables. Define and explain selection bias? Explain it’s working. Classification is very important in machine learning. Define confounding variables.

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The MLOps Blog

JUNE 6, 2023

Bookmark for later Building MLOps Pipeline for NLP: Machine Translation Task [Tutorial] Building MLOps Pipeline for Time Series Prediction [Tutorial] Why do we need a model training pipeline? For each step of the tutorial, I’ll explain what is being done and will break down the code for you to make it easier to understand.

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How to Learn Machine Learning

APRIL 10, 2025

Faster Time-to-Market The built-in SageMaker algorithms together with auto-tuning capabilities provided by SageMaker Autopilot enable users to choose from pre-written algorithms for standard classification, regression, NLP problem sets or enable automated model selection and tuning functions.

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