Update README.md

README.md

@@ -6,12 +6,66 @@ If you find any problems with the code or have any ideas on improving it, please
 
 ## Penguins
 
-During this program we'll create a [SageMaker Pipeline](https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-sdk.html) to build an end-to-end Machine Learning system to solve the problem of classifying penguin species.
+During this program, we'll create a [SageMaker Pipeline](https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-sdk.html) to build an end-to-end Machine Learning system to solve the problem of classifying penguin species.
 
 Here are the relevant notebooks:
 
 * The [Setup notebook](penguins/penguins-setup.ipynb): We'll use this notebook at the beginning of the program to setup SageMaker Studio. You only need to go through the code here once.
-* The [Penguins in Production notebook](penguins/penguins-cohort.ipynb): This is the main notebook we'll use during the program. Inside you'll find the code of every session. 
+* The [Penguins in Production notebook](penguins/penguins-cohort.ipynb): This is the main notebook we'll use during the program. Inside you'll find the code of every session.
+
+## Questions
+
+Answering these questions will help you understand the material discussed during this session. Notice that each question could have one or more correct answers.
+
+<div style="margin: 30px 0 10px 0;"><span style="font-size: 1.1em; padding:4px; background-color: #b8bf9f; color: #000;"><strong>Question 1.1</strong></span></div>
+
+What will happen if we apply the SciKit-Learn transformation pipeline to the entire dataset before splitting it?
+
+1. Scaling will use the global statistics of the dataset, leaking the mean and variance of the test samples into the training process.
+2. Imputing the missing numeric values will use the global mean, leading to data leakage.
+3. The transformation pipeline expects multiple sets so it wouldn't work.
+4. We will reduce the number of lines of code we need to transform the dataset.
+
+
+<div style="margin: 30px 0 10px 0;"><span style="font-size: 1.1em; padding:4px; background-color: #b8bf9f; color: #000;"><strong>Question 1.2</strong></span></div>
+
+A hospital wants to predict which patients are prone to get a disease based on their medical history. They use weak supervision to label the data using a set of heuristics automatically. What are some of the disadvantages of weak supervision?
+
+1. Weak supervision doesn't scale to large datasets.
+2. Weak supervision doesn't adapt well to changes requiring relabeling.
+3. Weak supervision produces noisy labels.
+4. We might be unable to use weak supervision to label every data sample.
+
+
+<div style="margin: 30px 0 10px 0;"><span style="font-size: 1.1em; padding:4px; background-color: #b8bf9f; color: #000;"><strong>Question 1.3</strong></span></div>
+
+When collecting the information about the penguins, the scientists encountered a few rare species. To prevent these samples from not showing when splitting the data, they recommended using Stratified Sampling. Which of the following statements about Stratified Sampling are correct?
+
+1. Stratified Sampling assigns every sample of the population an equal chance of being selected.
+2. Stratified Sampling preserves the original distribution of different groups in the data.
+3. Stratified Sampling requires having a larger dataset compared to Random Sampling.
+4. Stratified Sampling can't be used when is not possible to divide all samples into groups.
+
+
+<div style="margin: 30px 0 10px 0;"><span style="font-size: 1.1em; padding:4px; background-color: #b8bf9f; color: #000;"><strong>Question 1.4</strong></span></div>
+
+Using more features to build a model will not necessarily lead to better predictions. Which of the following are drawbacks from adding more features?
+
+1. More features in a dataset increases the opportunity for data leakage.
+2. More features in a dataset increases the opportunity for overfitting.
+3. More features in a dataset increases the memory necessary to serve a model.
+4. More features in a dataset increases the development and maintenance time of a model. 
+
+
+<div style="margin: 30px 0 10px 0;"><span style="font-size: 1.1em; padding:4px; background-color: #b8bf9f; color: #000;"><strong>Question 1.5</strong></span></div>
+
+A bank wants to store every transaction they handle in a set of files in the cloud. Each file will contain the transactions generated in a day. The team who will manage these files wants to optimize the storage space and downloding speed. What format should the bank use to store the transactions?
+
+1. The bank should store the data in JSON format.
+2. The bank should store the data in CSV format.
+3. The bank should store the data in Parquet format.
+4. The bank should store the data in Pandas format.
+
 
 ## Pipeline of Digits