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Text Classification in NLP using Cross Validation and BERT

Mlearning.ai

Uysal and Gunal, 2014). Submission Suggestions Text Classification in NLP using Cross Validation and BERT was originally published in MLearning.ai Introduction In natural language processing, text categorization tasks are common (NLP). Please do follow my page if you gained anything useful from the article. Dönicke, T.,

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Best Egg achieved three times faster ML model training with Amazon SageMaker Automatic Model Tuning

AWS Machine Learning Blog

Since March 2014, Best Egg has delivered $22 billion in consumer personal loans with strong credit performance, welcomed almost 637,000 members to the recently launched Best Egg Financial Health platform, and empowered over 180,000 cardmembers who carry the new Best Egg Credit Card in their wallet.

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Time Series Forecasting with XGBoost and LightGBM: Predicting Energy Consumption

Mlearning.ai

For the purposes of this tutorial, I’ve chosen the London Energy Dataset which contains the energy consumption of 5,567 randomly selected households in the city of London, UK for the time period of November 2011 to February 2014. Grid search utilizes cross validation too, so it is crucial to provide an appropriate splitting mechanism.

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New Data Challenge: Aviation Weather Forecasting Using METAR Data

Ocean Protocol

The data we use for this challenge is Miami's historical METAR logs from 2014–2023. After that, you can train your model, tune its parameters, and validate its performance using metrics like RMSE, MAE, or MAPE. It’s also a good practice to perform cross-validation to assess the robustness of your model.