xa assignment 1
Q1 Keras and the MNIST Dataset (Optional)
Summarize all the results for the MNIST Dataset – http://yann.lecun.com/exdb/mnist/
Q2: Analyze the MNIST Dataset with Keras
Show screen shots to show installation Explain your results
Hint – use the following links
https://www.kaggle.com/ritupande/self-tutorial-deep-learning-using-keras/data
Install keras on anaconda – https://anaconda.org/conda-forge/keras
Q3. Redo MNIST Dataset with CNN
Hint – use the following links
https://www.kaggle.com/moghazy/guide-to-cnns-with-data-augmentation-keras
Q4 Use Tensorflow play to provide insights on how Tensorflow works –
Q5. Recommendation system with Tensorflow (Optional)
Go through the following tutorial to do the recommendation system with Tensorflow
https://developers.google.com/machine-learning/recommendation/
Q6 Do the XGBoost Exercise on the Titanic dataset
Install XGBoost on anaconda – https://anaconda.org/conda-forge/xgboost
hint on link –
https://www.kaggle.com/ihopethiswillfi/titanic-survival-prediction-in-python-with-xgboost
Q7 Apply XGBoost to Churn Modelling (same dataset as for ANN from previous week’s exercise)
And compare results to the ANN algorithm
Q7 XGBoost for Churn Modelling.zip
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