应用机器学习课程
应用机器学习课程可以帮助您学习数据预处理、模型选择、Feature Engineering 和 Evaluation 指标。您可以掌握在实际环境中实施算法、优化性能和解释结果的技能。许多课程介绍 Python、TensorFlow 和 Scikit-learn 等工具，这些工具支持开发机器学习模型和应用 AI 技术解决实际问题。
热门应用机器学习课程和认证
状态：预览DeepLearning.AI
您将获得的技能: Deep Learning, Artificial Neural Networks, Artificial Intelligence, NumPy, Computer Vision, Supervised Learning, Linear Algebra, Calculus
状态：预览University of Illinois Urbana-Champaign
您将获得的技能: 心理学, 学习理论, 教学法, 学校心理学, 高等教育, 人类发展, 教育软件和技术, 社会科学, 教育与培训, 儿童发展
您将获得的技能: PyTorch (Machine Learning Library), Convolutional Neural Networks, Heat Maps, Model Evaluation, Image Analysis, Deep Learning, Computer Vision
您将获得的技能: Deep Learning, Tensorflow, Keras (Neural Network Library), Matplotlib, NumPy, Artificial Neural Networks, Python Programming, Pandas (Python Package), Data Science, Artificial Intelligence, Data Preprocessing, Machine Learning, Data Manipulation, Model Evaluation, Classification Algorithms
状态：免费试用Macquarie University
您将获得的技能: 编写培训材料, 促进讨论, 协作软件, 信息图表, 内容创作, 故事板, 建设性反馈, 设计评论, 教学法, 多媒体, 规划, 教育软件和技术, 数字教学法, 视频制作, 播客, 教学设计, 教学, 虚拟环境, 课程开发, 学习管理系统
状态：预览University of Colorado Boulder
您将获得的技能: 网页内容无障碍指南, 数字教学法, 教育软件和技术, 课程开发, 语言学习, 混合式学习, 技术战略
状态：免费试用您将获得的技能: 卷积神经网络, PyTorch（机器学习库）, 数据管道, 模型部署, Python 程序设计, 视觉转换器（ViT）, 迁移学习, 深度学习, Keras（神经网络库）, 数据预处理, 地理空间信息与技术, 模型评估, 机器学习, 计算机视觉
状态：新状态：预览您将获得的技能: Feature Engineering, Deep Learning, PyTorch (Machine Learning Library), Convolutional Neural Networks, Natural Language Processing, Data Preprocessing, Artificial Neural Networks, Transfer Learning, Recurrent Neural Networks (RNNs), Artificial Intelligence, Computer Vision, Jupyter, Predictive Modeling, Machine Learning, Model Evaluation, Data Transformation
状态：免费试用University of Alberta
您将获得的技能: Algorithm, 模拟, 强化学习, 人工神经网络, 马尔可夫模型, 机器学习算法, 机器学习, 模型评估, 性能调整, 性能测试, 人工智能和机器学习（AI/ML）
Coursera
您将获得的技能: Keras (Neural Network Library), Deep Learning, Tensorflow, Artificial Neural Networks, Machine Learning, Data Preprocessing, Model Evaluation
状态：预览Universidad de los Andes
您将获得的技能: Recurrent Neural Networks (RNNs), Deep Learning, Convolutional Neural Networks, Generative Model Architectures, Generative Adversarial Networks (GANs), Transfer Learning, Vision Transformer (ViT), Image Analysis, Artificial Neural Networks, Machine Learning Methods, Computer Vision, Network Architecture, Natural Language Processing
状态：预览Northeastern University
您将获得的技能: Model Evaluation, Linear Algebra, Statistical Machine Learning, Probability, Bayesian Statistics, Probability Distribution, Mathematical Modeling, Machine Learning, Applied Mathematics, Statistical Inference, Dimensionality Reduction, Algebra
总之，以下是 10 最受欢迎的 applied machine learning 课程
- Neuronale Netze und Deep Learning: DeepLearning.AI
- 学习、知识和人类发展: University of Illinois Urbana-Champaign
- Deep Learning with PyTorch : GradCAM: Coursera
- Deep Learning - Crash Course 2023: Packt
- 教育工作者在线学习设计: Macquarie University
- 混合式语言学习：教师的设计与实践: University of Colorado Boulder
- 使用深度学习的人工智能顶点项目: IBM
- Deep Learning: Build & Optimize Neural Networks: EDUCBA
- 完整的强化学习系统（Capstone）: University of Alberta
- Curso Completo de Deep Learning: Coursera
