Machine Learning A-Z: Logistic Regression Using Python ©
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Brief Introduction
The Complet Logistic Regression Course from Scratch with Python, NumPy, Pandas, Matplotlib, Scikit-Learn and more!Description
Are you ready to start your path to becoming a Machine Learning expert!
Are you ready to train your machine like a father trains his son!
"A breakthrough in Machine Learning would be worth ten Microsofts." -Bill Gates
There are lots of courses and lectures out there regarding logistic regression. This course is different!
This course is truly a step-by-step. In every new tutorial we build on what had already learned and move one extra step forward and then we assign you a small task that is solved in the beginning of next video.
We start by teaching the theoretical part of concept and then we implement everything as it is practically using python
This comprehensive course will be your guide to learning how to use the power of Python to train your machine such that your machine starts learning just like human and based on that learning, your machine starts making predictions as well!
We’ll be using python as programming language in this course which is the hottest language nowadays if we talk about machine leaning. Python will be taught from very basic level up to advanced level so that any machine learning concept can be implemented.
We’ll also learn various steps of data pre processing which allows us to make data ready for machine learning algorithms.
We’ll learn all general concepts of machine learning overall which will be followed by the implementation of one of the most important ML algorithm “Logistic regression”. Each and every concept of logistic regression will be taught theoretically and will be implemented using python.
Machine learning has been ranked one of the hottest jobs on Glassdoor and the average salary of a machine learning engineer is over $110,000 in the United States according to Indeed! Machine Learning is a rewarding career that allows you to solve some of the world's most interesting problems!
This course is designed for both beginners with some programming experience or even those who know nothing about ML and Logistic Regression!
This comprehensive course is comparable to other Machine Learning courses that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 50 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for Logistic regression and machine learning on Udemy!
We'll teach you how to program with Python, how to use it for data pre processing and logistic regression! Here a just a few of the topics we will be learning:
Programming with Python
NumPy with Python for array handling
Using pandas Data Frames to handle Excel Files
Use matplotlib for data visualizations
Data Pre processing
Machine Learning concepts, including:
Training and testing sets
Model training
Model Validation
Logistic regression with sk-learn
Logistic regression from absolute scratch
Implementing logistic regression on different data sets
and much, much more!
Enroll in the course and become a data scientist today!
Who this course is for:
This course is for you if you want to learn how to program in Python for Machine Learning
This course is for you if you want to make a predictive analysis model
This course is for you if you are tired of Machine Learning courses that are too complicated and expensive
This course is for you if you want to learn Python by doing
This course is for someone who is absolute beginner and have very little idea of machine learning
This course is for someone who want to learn Logistic regression from zero to hero
Requirements
- No prior knowledge or experience needed. Only a passion to be successful!
- Admin permissions to download files
Knowledge
- Learn basics of logistic regression
- Learn how to implement logistic regression on any data set
- Learn to create a complete structure for logistic regression from scratch using python
- Use SciKit-Learn for Logistic Regression
- Learn how to extend a binary class classifier to multi class classifier
- Learn and implement concepts like sigmoid, decision boundary, cost function and gradient decent using python
- Learn the basics of Machine Learning
- Learn all terminologies and main concepts of Machine learning theoretically
- Learn Data Normalization/scaling using python
- Learn how to install packages in Python
- Learn Data Visualization using python
- Learn to program in Python at a good level
Outline
- Course Introduction
- Introduction
- Motivation for this Course
- Past, Present and future of Machine Learning
- Course Overview
- Link to the Python codes for the projects and the data
- Please Help Us Growth
- Introduction to Python
- Hello World
- Introduction to data types
- Numbers
- Strings
- Tuples
- Lists
- Dictionaries
- Sets
- Comparison Operators
- Logical Operators, User Input, Game
- Decision Making (1)
- Decision Making (2)
- Better Coding Practice, Completing the Game
- For Loop
- While Loop
- Simple Functions
- Boolian and Value returning Function
- Calculator Project
- Introduction to Machine Learning for Beginners
- Introduction to Machine Learning for Beginners
- Kids Vs Computer Learning
- Dataset
- Labels and Features
- Train Test Split
- Outliers
- Model and Training
- Overfitting and Underfitting
- Accuracy and Error
- Formates Data
- Types of Learning
- Classsification Vs Regression
- Clustering
- Recap, Flow of Machine Learning Project
- Logistic Regression Step-by-Step
- Introduction to Logistic Regression and Motivation
- Pros and Cons
- Introduction to the final Project
- Numpy
- Pandas (1)
- Pandas (2)
- Reading and Manipulating Dataset
- Matplotlib (1)
- Matplotlib (2)
- Dealing with Missing Values
- Outliers Removal
- Categorical to Numeric
- ScikitLearn - Quick Implementation of Logistic Regression
- Sigmoid Function
- Decision Boundary
- Cost Function
- Gradient Decent
- Logistic Regression from Scratch (1)
- Logistic Regression from Scratch (2)
- Logistic Regression from Scratch (3)
- Logistic Regression from Scratch (4)
- Logistic Regression from Scratch (5)
- Logistic Regression from Scratch (6)
- Binary to Multiclass
- Conclusion and Bonus Lectures
- Concluding and Remarks
- Free Gift
- More about AI Sciences Learning Company
AI Sciences
4.1 Raiting
Machine Learning A-Z: Logistic Regression Using Python ©
- 4.1
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The Complet Logistic Regression Course from Scratch with Python, NumPy, Pandas, Matplotlib, Scikit-Learn and more! Are you ready to start your path to becoming a Machine Learning expert!...
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