Logistic Regression with Python and Numpy

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Implement Logistic Regression using Python and Numpy.

Apply Logistic Regression to solve binary classification problems.

Clock2 hours
Intermediate중급
Cloud다운로드 필요 없음
Video분할 화면 동영상
Comment Dots영어
Laptop데스크톱 전용

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. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, NumPy, and Seaborn pre-installed.

개발할 기술

  • Deep Learning
  • Machine Learning
  • Logistic Regression
  • Python Programming
  • Numpy

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

  1. Introduction

  2. Hyperparameters

  3. Dataset

  4. A Mini Batch of Examples

  5. Create Model

  6. Forward Pass

  7. Backward Pass

  8. Update Parameters

  9. Check Model Performance

  10. Training Loop

안내형 프로젝트 진행 방식

작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.

검토

LOGISTIC REGRESSION WITH PYTHON AND NUMPY의 최상위 리뷰

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