机器学习

机器学习课程介绍如何创建使用和分析大规模数据的系统。具体内容包括预测算法、自然语言处理以及统计模式识别。

...
机器学习
Stanford University
机器学习
课程
Neural Networks and Deep Learning
deeplearning.ai
Neural Networks and Deep Learning
课程
Natural Language Processing with Classification and Vector Spaces
deeplearning.ai
Natural Language Processing with Classification and Vector Spaces
课程
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
deeplearning.ai
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
课程
Mathematics for Machine Learning: Linear Algebra
Imperial College London
Mathematics for Machine Learning: Linear Algebra
课程
Structuring Machine Learning Projects
deeplearning.ai
Structuring Machine Learning Projects
课程
Convolutional Neural Networks
deeplearning.ai
Convolutional Neural Networks
课程
Convolutional Neural Networks in TensorFlow
deeplearning.ai
Convolutional Neural Networks in TensorFlow
课程
Natural Language Processing with Probabilistic Models
deeplearning.ai
Natural Language Processing with Probabilistic Models
课程
Machine Learning with Python
IBM
Machine Learning with Python
课程
Sequence Models
deeplearning.ai
Sequence Models
课程
Natural Language Processing in TensorFlow
deeplearning.ai
Natural Language Processing in TensorFlow
课程
Fundamentals of Reinforcement Learning
University of Alberta
Fundamentals of Reinforcement Learning
课程
AI for Medical Diagnosis
deeplearning.ai
AI for Medical Diagnosis
课程
Google Cloud Platform Big Data and Machine Learning Fundamentals
Google Cloud
Google Cloud Platform Big Data and Machine Learning Fundamentals
课程
Introduction to Artificial Intelligence (AI)
IBM
Introduction to Artificial Intelligence (AI)
课程
Machine Learning for Business Professionals
Google Cloud
Machine Learning for Business Professionals
课程
Foundations of Data Science: K-Means Clustering in Python
University of London
Foundations of Data Science: K-Means Clustering in Python
课程
Sequences, Time Series and Prediction
deeplearning.ai
Sequences, Time Series and Prediction
课程

    关于 机器学习 的常见问题

  • Machine learning is a branch of artificial intelligence that seeks to build computer systems that can learn from data without human intervention. These powerful techniques rely on the creation of sophisticated analytical models that are “trained” to recognize patterns within a specific dataset before being unleashed to apply these patterns to more and more data, steadily improving performance without further guidance.

    For example, machine learning is making increasingly accurate image recognition algorithms possible. Human programmers provide a relatively small set of images that are labeled as “cars” or “not cars,” for instance, and then expose the algorithms to vastly larger numbers of images to learn from. While the iterative algorithms typically used in machine learning aren’t new, the power of today’s computing systems have enabled this method of data analysis to become more effective more rapidly than ever.