Welcome to this project-based course on Logistic with NumPy and Python. In this project, you will do all the machine learning without using any of the popular machine learning libraries such as scikit-learn and statsmodels. The aim of this project and is to implement all the machinery, including gradient descent, cost function, and logistic regression, of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals. By the time you complete this project, you will be able to build a logistic regression model using Python and NumPy, conduct basic exploratory data analysis, and implement gradient descent from scratch. The prerequisites for this project are prior programming experience in Python and a basic understanding of machine learning theory.
Logistic Regression with NumPy and Python
Logistic Regression with NumPy and Python
ไฝๆๅธ๏ผSnehan Kekre
่ฎฟ้ฎๆ้็ฑ New York State Department of Labor ๆไพ
13,833 ไบบๅทฒๆณจๅ
๏ผ396 ๆก่ฏ่ฎบ๏ผ
ๆจ่ไฝ้ช
ๆจๅฐๅญฆๅฐไปไน
Implement the gradient descent algorithm from scratch
Perform logistic regression with NumPy and Python
Create data visualizations with Matplotlib and Seaborn
ๆจๅฐ็ปไน ็ๆ่ฝ
- Machine Learning
- Logistic Regression
- Machine Learning Algorithms
- Data Analysis
- NumPy
- Data Science
- Jupyter
- Seaborn
- Python Programming
- Algorithms
- Classification Algorithms
- Supervised Learning
- Matplotlib
- Data Visualization
- ๆ่ฝ้จๅๅทฒๆๅ ใๆพ็คบ 12 ้กนๆ่ฝ๏ผๅ ฑ 14 ้กนใ
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ๅจ 2 ๅฐๆถๅ ๅญฆไน ใ็ปไน ๅนถๅบ็จๅฒไฝๅฟ ๅคๆ่ฝ
- ๆฅๅ่กไธไธๅฎถ็ๅน่ฎญ
- ่ทๅพ่งฃๅณๅฎ่ฎญๅทฅไฝไปปๅก็ๅฎ่ทต็ป้ช
- ไฝฟ็จๆๆฐ็ๅทฅๅ ทๅๆๆฏๆฅๅปบ็ซไฟกๅฟ
ๅ ณไบๆญคๆๅฏผ้กน็ฎ
ๅๆญฅ่ฟ่กๅญฆไน
ๅจไธๆจ็ๅทฅไฝๅบไธ่ตทๅจๅๅฑไธญๆญๆพ็่ง้ขไธญ๏ผๆจ็ๆ่ฏพๆๅธๅฐๆๅฏผๆจๅฎๆๆฏไธชๆญฅ้ชค๏ผ
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Introduction and Project Overview
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Load the Data and Import Libraries
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Visualize the Data
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Define the Logistic Sigmoid Function ๐(๐ง)
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Compute the Cost Function ๐ฝ(๐) and Gradient
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Cost and Gradient at Initialization
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Implement Gradient Descent
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Plotting the Convergence of ๐ฝ(๐)
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Plotting the Decision Boundary
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Predictions Using the Optimized ๐ Values
ๆจ่ไฝ้ช
Prior programming experience in Python and machine learning theory is recommended.
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- 4 stars
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ๆพ็คบ 3/396 ไธช
ๅทฒไบ Aug 29, 2020ๅฎก้
Very helpful for learning logistic regression without using any libraries. Before taking this project one should have a clear understanding of Logistic Regression, then it will be very helpful
ๅทฒไบ Jul 14, 2020ๅฎก้
Gain more understanding about LR and gradient descent practically.
ๅทฒไบ May 23, 2020ๅฎก้
Its a good course. Instructor is good. Lot of concepts cleared and enough practice has done.
