Linear regression is commonly used to quantify the relationship between two or more variables. It is also used to adjust for confounding.
Regression is the study of dependence — A Predictive modelling technique
— Example: Relationship between Age & Income
2. To forecast effects
— Example: Effect on sale income for 1000$ spent on marketing
3. To forecast trends
— Example: Predicting price of bitcoin in the next 6 months
2. Data Quality:
3. Computational Complexity:
4. Comprehensible & Transparent:
An overview of the oldest supervised machine-learning algorithm, its type & shortcomings.
Learning is a new fun in the field of Machine Learning and Data Science. In this article, we’ll be discussing 15 machine learning and data science projects.
I decided to write few brief articles regarding this topic, which are intended to help people new to this topic dive in the interesting world of Machine Learning. Today we go further, and tackle Linear Regression, another extremely popular and wide used technique.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant
Regression(Data Science Part 6) Linear Regression with Math (6.1) ... Now, we will understand all parts and types of regression in detail.