Regression, Classification, -Series , NLP. Not for bners.

Learn how to build a Data Science project by theirselves

Learn how to analyze the Machine Learning models performance

Learn how to apply Machine Learning Algorithms

Learn perfog Data Analysis and Feature Eeering

Some knowledge of Data Science and Python.

Willingness to learn how to build a Data Science Project.

Welcome to the Data Science Projects 2 - Data Analysis & Machine Learning course. This is the second course for data science projects which we will be working with another 4 datasets. This is not a bner level course. This course is built for the students who learned python for data science and wants to apply what they learned but don't know where to start or for the ones who wants to practice and test their knowledge. In this course we will be building 4 data science projects which are going to be Regression, Classification, -Series and NLP projects. We will be covering Linear Regression, Logistic Regression, K Nearest Neighbors, Support Vector Machines, Decision Tree, Random Forests, ARIMA, Text Classification and Sennt Analysis as machine learning algorithms in our course. All projects are going to be end to end so it will be easy to follow what we are doing step by step and I will be giving short explanations for the codes that i write. Main motivation of this course is teaching students how to do projects by theirselves. By taking this course you will be experienced in data science projects and you can apply the codes by yourself in order to build yor own project. Building projects is one of the most important ways to get into and learn Data Science. Thanks for reading, if you are interested in Data Science lets meet in the first lesson.

Section 1: First Lecture

Lecture 1 First Lecture

Section 2: Employee Performance Score Classification

Lecture 2 You can  the data set

Lecture 3 Data Analysis part 1

Lecture 4 Data Analysis part 2 and Feature Eeering

Lecture 5 Machine Learning

Section 3: Real Estate Project - Regression

Lecture 6 You can  the data set

Lecture 7 Data Analysis

Lecture 8 Feature Eeering

Lecture 9 Machine Learning

People who learned data science and want to see how it is used in projects

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