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Non-linear regression is a powerful technique used in statistics and machine learning to model and analyze complex relationships between variables. Unlike linear regression, which assumes a linear relationship between the independent and dependent variables, non-linear regression algorithms can capture more intricate and non-linear patterns. This makes them particularly useful when dealing with real-world phenomena where linear relationships are insufficient. Following Non-Linear regression models are covered in the attached Jypter notebook...

During my participation in the MIT-GreatLearning Applied Data Science Program, I experienced an intensive curriculum that encompassed diverse subjects such as Statistics, Python programming, Machine Learning, Neural Networks, and Recommendation Systems. The culmination of the program was the Capstone project, which aimed to predict Loan Default. This involved crucial steps like Data Preparation, Exploratory Data Analysis, constructing models, and generating a comprehensive performance report for the various models employed. The final outcome is a binary classification....

During an interview process, interviewers generally ask and expect textbook definitions of basic terms. Interviewees, on the other hand must be prepared and answer them promptly. Lengthy and exploratory answers prevent interviewers from asking more probing questions. Confidence Interval A confidence interval is a range of values around the point estimate, constructed so that this range will contain the population parameter with a certain degree of confidence, expressed in percentage terms....