Data Science Projects 3 - Data Analysis & Machine Learning

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