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Published 12/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 375.64 MB | Duration: 1h 27m
Learn how to build Data Science Projects with Python. Regression, Classification, Time-Series , NLP. Not for beginners.
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 375.64 MB | Duration: 1h 27m
Learn how to build Data Science Projects with Python. Regression, Classification, Time-Series , NLP. Not for beginners.
What you'll learn
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 performing Data Analysis and Feature Engineering
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 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 beginner 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, 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: First Lecture
Lecture 1 First Lecture
Section 2: Employee Performance Score Classification
Lecture 2 You can download the data set
Lecture 3 Data Analysis part 1
Lecture 4 Data Analysis part 2 and Feature Engineering
Lecture 5 Machine Learning
Section 3: Real Estate Project - Regression
Lecture 6 You can download the data set
Lecture 7 Data Analysis
Lecture 8 Feature Engineering
Lecture 9 Machine Learning
People who learned data science and want to see how it is used in projects
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