Thanks!

[coderschoolreview]

The goal of this assignment is focus on:

• Take a step further into visualization world.
• How to split your data into train and test part
• Correlation between each feature columns and label column
• Build your first model linear regression and try some methods to evaluate (MAE, MSE, RMSE)
• Make some insights and conclusion about the data

Things you did well:

• You can actually load data and perform simple visualization steps.
• More familiar with seaborn, it's a library built on top matplotlib, very powerful and great potential for visualize task. Visualization plays an important role in data science. It's not only help you understand data but also a good way to explain the problem to your client, your boss.

Things to work on:

• You need to practice more and complete the whole assignment as it will provide you useful experience. :)
• Try your best to get used to the concept of training+testing set and fitting machine learning model.

Keep up the good work. You’re getting better and better.

[coderschoolreview]

The goal of this assignment is focus on

• Get to know about NLP techniques
• Understand the concept of classification problem
• Evaluate the classification result with Accuracy, Precision and Recall
• Build your first model logistic regression

Things you did well:

• Understand the basic flow to deal with classification task
• Be familiar with the techniques of NLP
• You get used to dealing with train/test split concept and evaluating results with accuracy reports

Things to work on:

• You need to understand the meaning of each step in this exercise (not only copy and paste)
• Revise the notebook to be more comprehensive and extract more information from the results
• You should recap everything you understand, not only just run codes.

In summary, you did a great job and improved very significantly :). Keep up with the final project !!!.