Predictive Modelling In Data Science By Spotle

What you'll learn
Regression Analysis
Logistic Regression
Ridge Regression
Generalized Linear Model Or GLM Regression
Requirements
You will need to have a computer or a mobile handset with an internet connection
Description
In this Spotle masterclass you will learn:The predictive modeling, for a rewarding career in data science.Techniques such as linear regression, logistics regression, ridge regression, GLM regression.At the end of this course you will build predictive models in Python.Data science and Python have become key industry drivers in the global job and opportunity market. This course with mix of lectures from industry experts and Ivy League academics will help students, recent graduates and young professionals learn predictive modelling and its applications in business scenarios using Python programming language. What is predictive modelling? Predictive modeling is a process that uses statistics, data mining and probability to forecast the future outcomes. Such as, let's say, an EdTech company is trying to assess the market. They have a question. The market condition that they predict will decide their future investment area. Their question is, is the future of learning going to be self-paced online? As we apply predictive modelling techniques on the available data from the market the predictive outcome to this question is 'Yes. The future of learning is going to be self-paced online'. Now the future will have the actual outcome. But the EdTech company will invest in this area as per this predictive outcome.
Overview
Section 1: Introduction
Lecture 1 Introduction To Data Science
Lecture 2 Introduction To Predictive Modelling
Section 2: Linear Regression
Lecture 3 Introduction To Linear Regression
Lecture 4 Fit Linear Regression Model To Data
Lecture 5 Model Complexity And Bias-Variance Trade-off
Lecture 6 Variable Selection
Lecture 7 Statistical Inference
Lecture 8 Multicollinearity
Lecture 9 Measures of Accuracy
Lecture 10 Understanding Linear Regression With Python
Section 3: Logistic Regression
Lecture 11 Introduction To Logistic Regression
Lecture 12 Likelihood Estimation
Lecture 13 Statistical Inference
Lecture 14 Measure Of Accuracy
Lecture 15 Understanding Logistic Regression With Python
Section 4: Ridge Regression
Lecture 16 Ridge Regression Part - 1
Lecture 17 Ridge Regression Part - 2
Section 5: Generalized Linear Models
Lecture 18 Generalized Linear Models
Lecture 19 Understanding Generalized Linear Models With Python
Anyone with an interest in a rewarding career in Data Science


Homepage

https://www.udemy.com/course/predictive-modelling-by-spotle/

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