Published 2/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 411.79 MB | Duration: 1h 22m

Learn how to build Data Science Projects with Python. Classification, Time-Series and NLP Projects. Not for beginners.
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 model performances
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 3 - Data Analysis & Machine Learning course. Data science projects course series is made from the projects that i built for my website and courses. 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 3 data science projects which are going to be Classification, Time-Series and NLP projects. We will be covering Linear Regression, Logistic Regression, K Nearest Neighbors, Support Vector Machines, Decision Tree, Random Forests, Autoregressive Models, 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 First Lecture
Section 2: Classification Project
Lecture 2 Data Set
Lecture 3 Data Analysis
Lecture 4 Data Analysis II
Lecture 5 Feature Engineering & Machine Learning
Section 3: Time Series Project
Lecture 6 Data Set
Lecture 7 Data Analysis
Lecture 8 Data Analysis II & Model Training
Section 4: Natural Language Processing (NLP) Project
Lecture 9 Data Set
Lecture 10 Data Analysis
Lecture 11 Sentiment Analysis
Lecture 12 Text Classification
Section 5: Bonus Section
Lecture 13 bonus lecture
People who are into Data Science,People who are into Data Analysis,People who are into Machine Learning
Screenshots