/Machine_Learning_Models

Machine Learning Projects

Machine Learning Projects

This contain the Machine Learning projects.

  1. Linear Regression module development using scipy module Details: Here we have used height-weight.csv dataset , by using this we have found out the relation between the height-weight . The various linear regression coeffienent i.e. slope and intercept are found out. And by using this eq. slope*x + intercept i.e. basic regression model we build. Refer file name :- Linear Regression Basic model for height-weight dataset.rar

  2. Exploratory Data Analysis Details: Here Exploratory Data Analysis is done on movie-lens dataset. Refer file name :- EDA_movie_lens_dataset.rar

  3. Airplane Crash Severity (Imbalance Classification) Prediction Details : Here the Airplane Crash dataset has been given which is imbalance data.We need to predict the severity of airplane crash. The dataset taken from HackerEarth ML Competition. Refer file name :- Severity Challenge.rar New modified algo - Severity Challenge-Part2.rar

  4. EDA and Aanlysis of Different Linear Regression Models Details : Different Linear Regression models are used for comparision for model performace and How EDA help us to analyz data,decision decision making,feature selection and feature engineering. Dataset used for this is auto-mpg.csv Refer file name :- Multivarient_LR.rar

  5. Concrete Strength Prediction Details : Modeling of strength of high performance concrete using Machine Learning need to be done. Refer file name :- concretestrength.rar

  6. Bank Loan Camp Details :This case is about a bank (Thera Bank) whose management wants to explore ways of converting its liability customers to personal loan customers (while retaining them as depositors). A campaign that the bank ran last year for liability customers showed a healthy conversion rate of over 9% success. This has encouraged the retail marketing department to devise campaigns with better target marketing to increase the success ratio with minimal budget. The classification goal is to predict the likelihood of a liability customer buying personal loans.

    Ref file : banlloancamp.rar

  7. CASE STUDY : EMPLOYEE ATTRITION CONTROL Deatils :Predicting which employees are prone to leave next using information from existing employees and those that had left Note : Ref file contain 2 submission file one with xgboost and one with lightgbm Ref File: utiva-python-bigdata-cohort1-20200304T094934Z-001.rar