Projects:• Title 1: People Analytics Project:(Analytical Project):Description: Our client was interested in promoting their business to the next level. They were in their venture of opening their franchise in multiple locations. So, the Human Resource department team approached us to gather insights. We as a team of 6 people build a model to predict whether the people will be happy if they are transferred to other locations.Tools: PythonLibraries: Pandas, numpy, matplotlib, Min-Max Scaler, seaborn, SMOTE, sklearnAlgorithm: KNN, Random Forest Classifier, Decision Tree Classifier, Naive Bayes, SVM, Logistic Regression.Title2: Forecasting Insurance Amount:Description: Our client is an Insurance company that has provided Home Insurance to its customers and they were in the process of providing automobile insurance to the customers as well. We, a team of 6 people, helped in building a model to predict whether the policyholders (customers) from the past year will also be interested in taking vehicle Insurance provided by the company.Tools used: PythonLibraries: Pandas,NumPy,matplotlib, seaborn, stats modelAlgorithm: Multiple Linear RegressionTitle 3: Customer Feedback Analysis: (Sentimental analysis):Our Client sales team worked closely with the customers to get feedback on their service. Information given by the users plays a very vital role in improving and developing their services. We as a team of 6 built a model in both machine learning as well as deep learning and were able to predict the customer's feedback and distinguish them as positive or negative.Tools used: PythonLibraries: Pandas, NumPy, sklearn, count vector, word cloudAlgorithm: Random Forest Classifier, NLP, TFIDF vectorizer, ANN

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