Logistic Regression 课程
Logistic Regression 课程可以帮助您学习统计建模、假设检验和系数解释。您可以掌握评估模型性能、理解几率比以及应用 Regularization 等技术提高准确性的技能。许多课程都会介绍 R、Python 等工具和 Scikit-learn 等专项库，展示这些技能如何用于分析医疗保健、金融和营销等各个领域的 Binary 结果。
热门 Logistic Regression 课程和认证
状态：免费试用您将获得的技能: Predictive Modeling, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Probability & Statistics, Statistical Inference, Business Analytics, Data Analysis, Statistical Analysis, Probability Distribution, Estimation, Machine Learning
状态：预览您将获得的技能: Data Preprocessing, Tensorflow, Scikit Learn (Machine Learning Library), Machine Learning, Feature Engineering, Deep Learning, Convolutional Neural Networks, Matplotlib, Jupyter, Python Programming, NumPy, Data Manipulation, Artificial Neural Networks, Seaborn, Development Environment, Pandas (Python Package), Regression Analysis
状态：新状态：免费试用您将获得的技能: Test Driven Development (TDD), Code Review, Continuous Delivery, Software Development Tools, Site Reliability Engineering, Regression Testing, Event Monitoring, Unit Testing, API Testing, Integration Testing, Incident Response, Performance Testing, Root Cause Analysis, Distributed Computing, CI/CD, Microservices
状态：新状态：免费试用您将获得的技能: Supervised Learning, Feature Engineering, Applied Machine Learning, Unsupervised Learning, Model Evaluation, Machine Learning Algorithms, Predictive Modeling, Data Preprocessing, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Performance Tuning
您将获得的技能: Supervised Learning, Data Preprocessing, Machine Learning, Machine Learning Algorithms, Time Series Analysis and Forecasting, Data Quality, Unsupervised Learning, Data Cleansing, Data Analysis, Feature Engineering, Data Transformation, Data Manipulation, Model Evaluation, Exploratory Data Analysis, Classification Algorithms, Regression Analysis
状态：新您将获得的技能: Pandas (Python Package), Data Manipulation, Jupyter, NumPy, Regression Analysis
状态：预览您将获得的技能: Model Evaluation, Supervised Learning, Data Preprocessing, Random Forest Algorithm, Applied Machine Learning, Decision Tree Learning, Feature Engineering, Machine Learning Algorithms, Classification Algorithms, Predictive Modeling, Data Analysis, Python Programming
状态：新状态：免费试用您将获得的技能: Classification And Regression Tree (CART), Decision Tree Learning, Classification Algorithms, Java, Java Programming, Machine Learning Algorithms, Supervised Learning, Algorithms, Machine Learning, Data Structures, Software Engineering
状态：新状态：免费试用Arizona State University
您将获得的技能: Bayesian Statistics, Statistical Modeling, Bayesian Network, Statistical Methods, Statistical Analysis, Data Analysis, R Programming, Data-Driven Decision-Making, Statistical Inference, Markov Model, Simulations, Probability Distribution
状态：新状态：预览Whizlabs
您将获得的技能: Supervised Learning, Unsupervised Learning, MLOps (Machine Learning Operations), Applied Machine Learning, Model Evaluation, AWS SageMaker, Data Preprocessing, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, Azure DevOps, Model Deployment, Microsoft Azure, Amazon Web Services, Deep Learning, Data Processing
状态：新状态：预览您将获得的技能: Test Case, Test Automation, Test Execution Engine, Regression Testing, CI/CD, API Testing, Continuous Integration, Continuous Deployment, No-Code Development, Test Planning, Test Data, Maintainability, Debugging, Scalability
状态：新状态：免费试用您将获得的技能: Java Programming, Java, Feature Engineering, Deep Learning, Data Pipelines
总之，以下是 10 最受欢迎的 logistic regression 课程
- Data Science Fundamentals Part 2: Unit 3: Pearson
- Master Machine Learning with TensorFlow: Basics to Advanced: EDUCBA
- Debugging & Testing for Software Delivery: Edureka
- Applied Machine Learning and Model Optimization: Packt
- DataPrep for H2O Driverless AI: H2O.ai
- Python for Data Visualization - A Beginner's Guide: Packt
- Python: Implement & Evaluate Random Forests for ML: EDUCBA
- Traverse Trees for ML with DFS & BFS: Coursera
- Bayesian Statistical Concepts and Methods: Arizona State University
- Fundamentals of Machine Learning: Whizlabs
