Review of Python Courses (Part 14)

In Part 13, I summarized my Datacamp courses 38-40. Today I will continue with the next three.

As a reminder, I introduced you to my recent work learning Python here.

My course #41 was Advanced Deep Learning with Keras. This course covers:

• Keras input and dense layers (from keras.layers import Input, Dense)
• Keras models (from keras.utils import plot_model)
• Fit and evaluate a model (from keras.models import Model)
• Category embeddings (from keras.layers import Embedding, Flatten)
• Shared layers
• Merge layers (from keras.layers import Add, Subtract)
• Fitting and predicting with multiple inputs
• Three-input models (from keras.layers import Concatenate)
• Summarizing and plotting models
• Stacking models
• Two-output models
• Single model for classification and regression (from keras.optimizers import Adam)

My course #42 was Working with the Statistical Simulation in Python. This course covers:

• Intro to Object Oriented Programming in Python
• Simulation basics [np.random.choice()]
• Using simulation for decision making
• Probability basics
• More probability concepts
• Data generating process
• eCommerce ad simulation
• Introduction to resampling methods
• Bootstrapping
• Jackknife resampling
• Permutation testing
• Advanced applications of simulation
• Monte Carlo integration
• Simulation for power analysis
• Applications in finance

My course #43 was Introduction to Predictive Analytics in Python. This course covers:

• Introduction and basetable structure
• Logistic regression (from sklearn import linear_model)
• Using the logistic regression model
• Variable selection
• Forward stepwise variable selection
• Deciding on the number of variables (from sklearn.cross_validation import train_test_split)
• The cumulative gains curve (import scikitplot as skplt)
• The lift curve
• Guiding business to better decisions
• Predictor insight graphs
• Discretization of continuous variables (pd.qcut(), pd.cut(), check_discretize)
• Preparing the predictor insight graph table (create_pig_table)
• Plotting the predictor insight graph

I will review more classes next time.