Data Science with Python Case Study 5: Read the datafile “letterCG.data” and set all the numerical attributes as features. For each of the wrong sample, plot the digit along with the predicted and original label. Compute the confusion matrix and count the number of instances that have gone wrong. Compare it with a model and also comment on the accuracy. Using scikit learn perform a PCA transformation such that the transformed dataset can explain 95% of the variance in the original dataset. Fit a logistic regression model and observe the accuracy. Load the digits dataset from sklearn and write a helper function to plot the image. Data Science with Python Case Study 4: Principal component analysis using scikit learn. Fit a random forest classifier and observe the accuracy. Fit a decision tree classifier and observe the accuracy. Replace the missing values by the most frequent value in each column. Load the data from ‘horses.csv’ and observe whether it contains missing values. Predict the survival of a horse based on various observed medical conditions. Compare the Error using two approaches – User Based Vs Item Based Data Science with Python Case Study 3: Handle missing values and fit a decision tree and compare its accuracy with a random forest classifier. The company is still unprofitable and is looking to improve both revenue and profit.

This will ensure that users are renting books based on their individual taste. You as an ML expert must model a recommendation engine so that the user gets a recommendation of books based on the behavior of similar users. So, the company makes more money when the user rents more books. The company charges a fixed fee per month plus rental per book. Data Science with Python Certification Case Study 2: BookRent is the largest online and offline book rental chain in India. You have to classify the plant leaves by various classifiers from different metrics of the leaves and to choose the best classifier for future reference. They have asked us to automate this process and remove any manual intervention from this process. A laborer from his experience decides the leaf type and subtype of the plant family.

Currently, the system they use to classify the trees which they import in a batch is quite manual. Below are few case studies, which are part of the Data Science with Python course curriculum: Data Science with Python Certification Case Study 1: Maple Leaves Ltd is a start-up company which makes herbs from different types of plants and its leaves. In addition, we also have 4 Projects that will enhance your implementation skills. Edureka's Data Science with Python certification course comprises of 40 case studies that will enrich your learning experience.

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