What you'll learn
Learn how to build a Data Science project by theirselves
Learn how to apply Machine Learning Algorithms
Learn performing Data Analysis and Feature Engineering
Learn how to analyze the Machine Learning models performance
Requirements
Some knowledge of Data Science and Python.
Willingness to learn how to build a Data Science Project.
Description
Welcome to the Data Science Projects - Data Analysis & Machine Learning 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, Time-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 Sentiment 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.
Overview
Section 1: Before Starting
Lecture 1 Before starting to the course
Section 2: PROJECT 1 - Market Sales Regression Analysis
Lecture 2 Get the data set
Lecture 3 Exploratory Data Analysis
Lecture 4 Feature Engineering
Lecture 5 Machine learning
Section 3: PROJECT 2- Car Purchasement Classification
Lecture 6 Get the data set
Lecture 7 Exploratory Data Analysis
Lecture 8 Feature Engineering
Lecture 9 Machine Learning part1
Lecture 10 Machine Learning part2
Section 4: PROJECT 3 - Gold Prices Analysis & Forecasting
Lecture 11 Get the data set
Lecture 12 Exploratory Data Analysis
Lecture 13 ARIMA Model
Section 5: PROJECT 4 - Hotel Reviews Sentiment Analysis and Classification
Lecture 14 Get the data set
Lecture 15 Exploratory Data Analysis
Lecture 16 Sentiment Analysis
Lecture 17 Text Classification
People who is into Data Science,People who is into Data Analysis,People who is into Machine Learning


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