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Python Machine Learning

필터링 기준

"python machine learning"에 대한 457개의 결과

University of Michigan
Applied Data Science with Python
획득할 기술: Algorithms, Applied Machine Learning, Artificial Neural Networks, Computational Logic, Computer Graphics, Computer Networking, Computer Programming, Data Analysis, Data Mining, Data Visualization, Econometrics, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Mathematical Theory & Analysis, Mathematics, Natural Language Processing, Network Analysis, Network Model, Plot (Graphics), Probability & Statistics, Programming Principles, Python Programming, Regression, Scikit-Learn, Statistical Machine Learning, Statistical Programming, Statistical Tests, Theoretical Computer Science
4.5
(32.1k개의 검토)
Intermediate · Specialization · 3-6 Months
University of Michigan
Applied Machine Learning in Python
획득할 기술: Probability & Statistics, Algorithms, Python Programming, Applied Machine Learning, Theoretical Computer Science, Regression, Econometrics, Computer Programming, Machine Learning, Artificial Neural Networks, Statistical Programming, Scikit-Learn, Machine Learning Algorithms, General Statistics
4.6
(8.1k개의 검토)
Intermediate · Course · 1-4 Weeks
IBM Skills Network
IBM Machine Learning
획득할 기술: Algebra, Algorithms, Analysis, Applied Machine Learning, Artificial Neural Networks, Bayesian Statistics, Business Analysis, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Data Analysis, Data Management, Data Structures, Data Visualization, Databases, Deep Learning, Dimensionality Reduction, Experiment, Exploratory Data Analysis, Feature Engineering, Forecasting, General Statistics, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematics, NoSQL, Probability & Statistics, Python Programming, Regression, Reinforcement Learning, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Theoretical Computer Science
4.6
(1k개의 검토)
Intermediate · Professional Certificate · 3-6 Months
IBM Skills Network
Machine Learning with Python
획득할 기술: Statistical Classification, Decision Tree, Supply Chain Systems, Algorithms, Probability & Statistics, Supply Chain and Logistics, Regression, Logistic Regression, K-Means Clustering, Data Management, Data Structures, General Statistics, Machine Learning Algorithms, Machine Learning, Entrepreneurship, Econometrics
4.7
(12.8k개의 검토)
Intermediate · Course · 1-3 Months
IBM Skills Network
IBM AI Engineering
획득할 기술: Algorithms, Apache, Applied Machine Learning, Artificial Neural Networks, Basic Descriptive Statistics, Big Data, Business Analysis, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Correlation And Dependence, Data Analysis, Data Clustering Algorithms, Data Management, Data Structures, Databases, Deep Learning, Dimensionality Reduction, Econometrics, Entrepreneurship, General Statistics, Machine Learning, Machine Learning Algorithms, Mathematics, NoSQL, Probability & Statistics, Probability Distribution, Python Programming, Regression, SQL, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Supply Chain Systems, Supply Chain and Logistics, Tensorflow, Theoretical Computer Science
4.6
(14.7k개의 검토)
Intermediate · Professional Certificate · 3-6 Months
DeepLearning.AI, Stanford University
Machine Learning
획득할 기술: Accounting, Algorithms, Applied Machine Learning, Artificial Neural Networks, Calculus, Communication, Computer Programming, Computer Vision, Cost, Data Analysis, Data Management, Data Mining, Data Structures, Deep Learning, Econometrics, Feature Engineering, General Statistics, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Operations Research, Probability & Statistics, Probability Distribution, Python Programming, Regression, Reinforcement Learning, Research and Design, Statistical Classification, Statistical Machine Learning, Statistical Programming, Strategy and Operations, Tensorflow, Theoretical Computer Science
4.9
(1.9k개의 검토)
Beginner · Specialization · 1-3 Months
University of Michigan
Introduction to Data Science in Python
획득할 기술: Numpy, Statistical Tests, Probability & Statistics, Computer Programming, Theoretical Computer Science, Mathematical Theory & Analysis, Data Analysis, Pandas, Computational Logic, Python Programming, Programming Principles, Analysis, Mathematics, Statistical Programming
4.5
(25.9k개의 검토)
Intermediate · Course · 1-4 Weeks
DeepLearning.AI
Neural Networks and Deep Learning
획득할 기술: Probability & Statistics, Mathematics, Entrepreneurship, Supply Chain Systems, Python Programming, Applied Machine Learning, Numpy, Computer Networking, Markov Model, Algorithms, Supply Chain, Logistic Regression, Supply Chain and Logistics, Theoretical Computer Science, Linear Algebra, Bayesian Statistics, Mathematical Theory & Analysis, Regression, Computer Architecture, Computational Logic, Network Model, Artificial Neural Networks, General Statistics, Computer Programming, Deep Learning, Machine Learning Algorithms, Machine Learning, Business Psychology, Hardware Design
4.9
(114.7k개의 검토)
Intermediate · Course · 1-4 Weeks
IBM Skills Network
IBM Data Science
획득할 기술: Algebra, Algorithms, Business Analysis, Communication, Computational Logic, Computer Programming, Computer Programming Tools, Correlation And Dependence, Data Analysis, Data Management, Data Mining, Data Structures, Data Visualization, Database Administration, Database Application, Databases, Econometrics, Entrepreneurship, Exploratory Data Analysis, Extract, Transform, Load, General Statistics, Geovisualization, Interactive Data Visualization, Machine Learning, Machine Learning Algorithms, Marketing, Mathematical Theory & Analysis, Mathematics, Modeling, Plot (Graphics), Probability & Statistics, Python Programming, R Programming, Regression, Regression Analysis, SPSS, SQL, Spreadsheet Software, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Supply Chain Systems, Supply Chain and Logistics, Theoretical Computer Science
4.6
(95.9k개의 검토)
Beginner · Professional Certificate · 3-6 Months
Google
Google IT Automation with Python
획득할 기술: Application Development, Cloud Computing, Cloud Platforms, Computational Logic, Computational Thinking, Computer Programming, Computer Programming Tools, Data Structures, Debugging, Github, Google Cloud Platform, Leadership and Management, Mathematical Theory & Analysis, Mathematics, Other Programming Languages, Programming Principles, Python Programming, Software Engineering, Software Engineering Tools, Software Testing, Statistical Programming, Theoretical Computer Science, Troubleshooting, Unit Testing
4.7
(31.3k개의 검토)
Beginner · Professional Certificate · 3-6 Months
DeepLearning.AI
Supervised Machine Learning: Regression and Classification
획득할 기술: Probability & Statistics, Python Programming, Mathematics, Probability Distribution, Statistical Machine Learning, Applied Machine Learning, Algorithms, Linearity, Regression, Theoretical Computer Science, Linear Algebra, Statistical Classification, Linear Regression, Computer Programming, Econometrics, Logistic Regression, Feature Engineering, Accounting, General Statistics, Statistical Programming, Calculus, Machine Learning, Cost, Artificial Neural Networks, Machine Learning Algorithms
4.9
(1.8k개의 검토)
Beginner · Course · 1-4 Weeks

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요약하자면, 여기에 가장 인기 있는 python machine learning 강좌 10개가 있습니다.

Applied Data Science with Python: University of Michigan
Applied Machine Learning in Python: University of Michigan
IBM Machine Learning: IBM Skills Network
Machine Learning with Python: IBM Skills Network
IBM AI Engineering: IBM Skills Network
Machine Learning: DeepLearning.AI
Introduction to Data Science in Python: University of Michigan
Neural Networks and Deep Learning: DeepLearning.AI
IBM Data Science: IBM Skills Network
Google IT Automation with Python: Google