The MNIST Dataset

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 -

•Tensor Flow Playground

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

Sample Solution

Aced Essays