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12.18 Making Predictions

This is the Section 12 which is going to describe Project 2 - Supervised Learning (Time Series Data - Regression) in details. Currently you are in Section 12: and Briefly describe sections are:- Data : https://github.com/gitShubhamSingh/data Section 1: Introduction Section 2: Machine Learning 101 (End to End) Section 3: Machine Learning and Data Science Framework Section 4: The 2 Paths Section 5: Data Science Environment Setup Section 6: Pandas Data Analysis Section 7: Numpy Section 8: Matplotlib Plotting and Data Visualization Section 9: Scikit-learn Creating Machine Learning Model Section 10: Supervised Learning Classification + Regression Section 11: Project 1 Supervised Learning ( Classification ) Section 12: Project 2 Supervised Learning ( Time Series Data - Regression) Section 13: Data Engineering Section 14: Neural Network, Deep Learning, Transfer Learning, TensorFlow Section 15: Story Telling + Communication How to present your work Section 16: Career Advice + Extra Bits Section 17: Learn Python Section 18: Learn Python Part 2 Section 19: Bonus Learn Advance Statistics and Mathematics Section 20: Where to Go from Here Section 21: Bonus Section Get Excited, Let's Start... Feature Scaling for machine learning : https://www.analyticsvidhya.com/blog/2020/04/feature-scaling-machine-learning-normalization-standardization/ Feature Scaling with scikit-learn : https://benalexkeen.com/feature-scaling-with-scikit-learn/ Feature Scaling why it is required : https://rahul-saini.medium.com/feature-scaling-why-it-is-required-8a93df1af310 Filling Missing Data with scikit-learn colab: https://colab.research.google.com/drive/162DyoCBFeufMjJI7n4XCiYpdqIdktZw_ ROC and AUC Curve : https://www.youtube.com/watch?v=4jRBRDbJemM Recieve Operating Characterstics (ROC) : https://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html Google Machine Learning (RAC and AUC) : https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc Bulldozer Price Prediction github : https://github.com/mrdbourke/zero-to-mastery-ml/blob/master/section-2-data-science-and-ml-tools/introduction-to-matplotlib-video.ipynb Kaggle Problem : https://www.kaggle.com/c/bluebook-for-bulldozers/overview Dog Breed Identification : https://www.dropbox.com/s/9kjr0ui9qbodfao/dog-breed-identification.zip?dl=0 Bulldozer Data : https://github.com/mrdbourke/zero-to-mastery-ml/raw/master/data/bluebook-for-bulldozers.zip kaggle-dataset-download-example : https://colab.research.google.com/drive/1jAVaZaoWicXLQphs4Uikg38UL_ED_5dC Pandas Catagorical : https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Categorical.html Bulldozer Price Prediction : https://github.com/mrdbourke/zero-to-mastery-ml/blob/master/section-3-structured-data-projects/end-to-end-bluebook-bulldozer-price-regression.ipynb

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16 просмотров
2 года назад
12+
16 просмотров
2 года назад

This is the Section 12 which is going to describe Project 2 - Supervised Learning (Time Series Data - Regression) in details. Currently you are in Section 12: and Briefly describe sections are:- Data : https://github.com/gitShubhamSingh/data Section 1: Introduction Section 2: Machine Learning 101 (End to End) Section 3: Machine Learning and Data Science Framework Section 4: The 2 Paths Section 5: Data Science Environment Setup Section 6: Pandas Data Analysis Section 7: Numpy Section 8: Matplotlib Plotting and Data Visualization Section 9: Scikit-learn Creating Machine Learning Model Section 10: Supervised Learning Classification + Regression Section 11: Project 1 Supervised Learning ( Classification ) Section 12: Project 2 Supervised Learning ( Time Series Data - Regression) Section 13: Data Engineering Section 14: Neural Network, Deep Learning, Transfer Learning, TensorFlow Section 15: Story Telling + Communication How to present your work Section 16: Career Advice + Extra Bits Section 17: Learn Python Section 18: Learn Python Part 2 Section 19: Bonus Learn Advance Statistics and Mathematics Section 20: Where to Go from Here Section 21: Bonus Section Get Excited, Let's Start... Feature Scaling for machine learning : https://www.analyticsvidhya.com/blog/2020/04/feature-scaling-machine-learning-normalization-standardization/ Feature Scaling with scikit-learn : https://benalexkeen.com/feature-scaling-with-scikit-learn/ Feature Scaling why it is required : https://rahul-saini.medium.com/feature-scaling-why-it-is-required-8a93df1af310 Filling Missing Data with scikit-learn colab: https://colab.research.google.com/drive/162DyoCBFeufMjJI7n4XCiYpdqIdktZw_ ROC and AUC Curve : https://www.youtube.com/watch?v=4jRBRDbJemM Recieve Operating Characterstics (ROC) : https://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html Google Machine Learning (RAC and AUC) : https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc Bulldozer Price Prediction github : https://github.com/mrdbourke/zero-to-mastery-ml/blob/master/section-2-data-science-and-ml-tools/introduction-to-matplotlib-video.ipynb Kaggle Problem : https://www.kaggle.com/c/bluebook-for-bulldozers/overview Dog Breed Identification : https://www.dropbox.com/s/9kjr0ui9qbodfao/dog-breed-identification.zip?dl=0 Bulldozer Data : https://github.com/mrdbourke/zero-to-mastery-ml/raw/master/data/bluebook-for-bulldozers.zip kaggle-dataset-download-example : https://colab.research.google.com/drive/1jAVaZaoWicXLQphs4Uikg38UL_ED_5dC Pandas Catagorical : https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Categorical.html Bulldozer Price Prediction : https://github.com/mrdbourke/zero-to-mastery-ml/blob/master/section-3-structured-data-projects/end-to-end-bluebook-bulldozer-price-regression.ipynb

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