Udemy - Automated Machine Learning with AutoGluon Library in Python

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[ DevCourseWeb.com ] Udemy - Automated Machine Learning with AutoGluon Library in Python
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1. Course Overview and Introduction
    • 1. Course Downloads and Files.html (1.3 KB)
    • 2. Course Welcome.mp4 (12.4 MB)
    • 3. Course Curriculum Overview.mp4 (45.2 MB)
    • 4. AutoGluon Overview.mp4 (40.6 MB)
    2. Tabular Data - Classification and Regression
    • 1. Introduction to Tabular Data Section.mp4 (19.1 MB)
    • 10. OPTIONAL Regression Metrics.mp4 (43.4 MB)
    • 11. AutoGluon Fit Parameters Inference Constraints and Manual Hyperparameters.mp4 (148.3 MB)
    • 12. Advanced AutoGluon Presets and Deployment.mp4 (75.3 MB)
    • 13. Advanced AutoGluon Custom Feature Engineering Pipeline.mp4 (65.5 MB)
    • 2. OPTIONAL Supervised Learning Overview.mp4 (96.0 MB)
    • 3. AutoGluon Classification Part One Data and Split.mp4 (98.5 MB)
    • 4. AutoGluon Classification Part Two Training the Model.mp4 (153.3 MB)
    • 5. OPTIONAL Train Test Splits and Cross-Validation.mp4 (38.4 MB)
    • 6. AutoGluon Classification Part Three Validation.mp4 (90.8 MB)
    • 7. AutoGluon Classification Part Four Interpretability.mp4 (92.0 MB)
    • 8. OPTIONAL Classification Metrics.mp4 (96.5 MB)
    • 9. AutoGluon Regression Data, Split, Training, and Validation.mp4 (106.9 MB)
    3. Multi-Modal Datasets
    • 1. Introduction to Multi-Modal Data Problems.mp4 (39.1 MB)
    • 2. Optional Download Trained Book Rating Prediction Model Here.html (0.3 KB)
    • 3. Natural Language - MultiClass Problem - Part One.mp4 (89.7 MB)
    • 4. Natural Language - MultiClass Problem - Part Two.mp4 (42.1 MB)
    • 5. Optional Download Trained Sentiment Analysis Model.html (0.6 KB)
    • 6. MultiModalPredictor on Binary Class with Natural Language Text.mp4 (123.4 MB)
    • book_rating
      • SummaryOfModels.html (9.0 KB)
      • __version__ (0.0 KB)
      • learner.pkl (2.2 MB)
      • metadata.json (8.3 KB)
      • models CatBoost
        • model.pkl (5.1 MB)
        LightGBM
        • model.pkl (4.4 MB)
        LightGBMLarge
        • model.pkl (38.5 MB)
        LightGBMXT
        • model.pkl (7.3 MB)
        NeuralNetTorch
        • model.pkl (605.5 KB)
        WeightedEnsemble_L2
        • model.pkl (8.5 KB)
        • utils
          • model_template.pkl (1.0 KB)
          • oof.pkl (20.0 KB)
          XGBoost
          • model.pkl (616.0 KB)
          • xgb.ubj (6.9 MB)
          • trainer.pkl (271.2 KB)
          • predictor.pkl (0.4 KB)
          • utils attr CatBoost
            • y_pred_proba_val.pkl (18.9 KB)
            LightGBM
            • y_pred_proba_val.pkl (18.9 KB)
            LightGBMLarge
            • y_pred_proba_val.pkl (18.9 KB)
            LightGBMXT
            • y_pred_proba_val.pkl (18.9 KB)
            NeuralNetTorch
            • y_pred_proba_val.pkl (18.9 KB)
            XGBoost
            • y_pred_proba_val.pkl (18.9 KB)
            data
            • X.pkl (115.2 MB)
            • X_val.pkl (12.9 MB)
            • y.pkl (144.1 KB)
            • y_val.pkl (16.6 KB)
            4. Time Series Forecasting
            • 1. Introduction to Time Series.mp4 (10.7 MB)
            • 2. Overview of Time Series in AutoGluon.mp4 (57.6 MB)
            • 3. Single Variate Time Series Forecasting in AutoGluon - Part One.mp4 (71.0 MB)
            • 4. Single Variate Time Series Forecasting in AutoGluon - Part Two.mp4 (71.0 MB)
            • 5. Single Variate Time Series Forecasting in AutoGluon - Part Three.mp4 (62.6 MB)
            • 6. Known Covariate Time Series Forecasting in AutoGluon - Part One.mp4 (114.6 MB)
            • 7. Known Covariate Time Series Forecasting in AutoGluon - Part Two.mp4 (34.8 MB)
            • 8. Past Covariate Time Series Forecasting.mp4 (49.0 MB)
            • Bonus Resources.txt (0.4 KB)

Description

Automated Machine Learning with AutoGluon Library in Python



https://DevCourseWeb.com

Published 4/2023
Created by Jose Portilla
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 31 Lectures ( 4h 51m ) | Size: 2 GB

Discover how to easily automate entire machine learning pipelines with the extremely powerful Autogluon library from AWS

What you'll learn
Understand the basics of the Autogluon Python library and its capabilities for automating machine learning tasks.
Learn how to install and set up the Autogluon Python library in your local environment.
Develop skills in data preparation and cleaning processes that are critical for successful machine learning outcomes using Autogluon.
Discover best practices for selecting and configuring machine learning models to achieve optimal results with minimal effort.
Explore how to use Autogluon to create high-accuracy models for image classification tasks, including object detection, segmentation, and classification.
Understand how to use Autogluon to perform natural language processing (NLP) tasks such as sentiment analysis.
Learn how to train and deploy time series models using Autogluon to make accurate predictions for future events or trends.
Gain hands-on experience in using Autogluon to analyze tabular data and build predictive models for business applications and financial forecasting.

Requirements
Some Python experience required.
Previous machine learning experience helpful, but no required.



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Udemy - Automated Machine Learning with AutoGluon Library in Python


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