EngineML: Hawk team

Classification:

1a: https://www.kaggle.com/pavanraj159/telecom-customer-churn-prediction/data 1b: https://www.kaggle.com/pavanraj159/loan-repayers-v-s-loan-defaulters-home-credit/notebook

Regression:

2a: https://www.kaggle.com/laowingkin/fifa-18-find-the-best-squad 2b: https://www.kaggle.com/ashishpatel26/home-credit-default-analysis 2c: https://www.kaggle.com/fabiendaniel/predicting-flight-delays-tutorial

Clustering:

3a: https://www.kaggle.com/thebrownviking20/k-means-clustering-of-1-million-headlines 3b: https://www.kaggle.com/fabiendaniel/customer-segmentation

Dimensionality Reduction:

4a: https://www.kaggle.com/arthurtok/interactive-intro-to-dimensionality-reduction 4b: https://www.kaggle.com/janiobachmann/credit-fraud-dealing-with-imbalanced-datasets

Reinforcement Learning:

5a: https://www.kaggle.com/osbornep/reinforcement-learning-for-meal-planning-in-python 5b: https://www.kaggle.com/aharless/logistic-of-genetic-features

Neural Networks:

6a: https://www.kaggle.com/kanncaa1/deep-learning-tutorial-for-beginners

Deep Learning:

7a: https://www.kaggle.com/jesperdramsch/intro-to-seismic-salt-and-how-to-geophysics 7b: https://www.kaggle.com/yassineghouzam/introduction-to-cnn-keras-0-997-top-6 7c: https://www.kaggle.com/raoulma/ny-stock-price-prediction-rnn-lstm-gru 7d: https://towardsdatascience.com/how-to-rapidly-test-dozens-of-deep-learning-models-in-python-cb839b518531

Ensembling - Model Comparison

8a: https://www.kaggle.com/serigne/stacked-regressions-top-4-on-leaderboard

Featuring Engineering:

9a: https://www.kaggle.com/abhishek/approaching-almost-any-nlp-problem-on-kaggle

Outlier Analysis:

10a: https://www.kaggle.com/shelars1985/anomaly-detection-using-gaussian-distribution 10b: https://www.kaggle.com/x09072993/aml-detection/notebook

Recommendation Engine:

11a: https://www.kaggle.com/fabiendaniel/film-recommendation-engine