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所在平台: Udemy |
课程主页: https://www.udemy.com/course/deep-learning-machine-learning-practical/
课程评论：没有评论
课程名称：机器学习实用训练营：8个真实项目 课程概述： 深度学习和机器学习是当前最热门的技术领域之一，正在迅速发展，提供丰富的职业机会。机器学习技术被广泛应用于多个行业，如银行、医疗、交通和科技等。机器学习是研究能够让计算机从经验中学习的算法，随着经验的增加（即更多的训练数据），计算机的性能能够持续提高。深度学习是机器学习的一个子集，通过多层人工神经网络进行操作，灵感来源于人脑结构，模仿生物神经元的工作方式。深度网络通过将多个人工神经元按层连接而成，增加隐藏层可以使网络更“深”，从而能够建模更复杂的非线性关系。深度学习广泛应用于自动驾驶汽车、面部和语音识别，以及医疗应用等。 本课程的目的是为学生提供深度和机器学习技术的关键方面的实用知识，以轻松、有趣的方式进行学习。课程为学生提供了实践经验，使用真实数据集训练深度和机器学习模型。课程涵盖了多种技术，并包含多个项目，具体包括但不限于： 1. 训练深度学习技术以执行图像分类任务。 2. 开发预测模型，使用最先进的Facebook Prophet时间序列预测未来商品价格等事件。 3. 开发自然语言处理模型，分析客户评论并识别垃圾/正常消息。 4. 开发推荐系统，如亚马逊和Netflix电影推荐系统。 本课程面向希望深入理解深度和机器学习模型的学生。建议拥有基本编程知识，但这些主题将在课程初期讲座中广泛讲解，因此课程没有先决条件，任何具有基本编程知识的学生均可参与。注册本课程的学生将掌握深度和机器学习模型，并能够直接将这些技能应用于解决实际挑战问题。
"Deep Learning and Machine Learning are one of the hottest tech fields to be in right now! The field is exploding with opportunities and career prospects. Machine/Deep Learning techniques are widely used in several sectors nowadays such as banking, healthcare, transportation and technology.Machine learning is the study of algorithms that teach computers to learn from experience. Through experience (i.e.: more training data), computers can continuously improve their performance. Deep Learning is a subset of Machine learning that utilizes multi-layer Artificial Neural Networks. Deep Learning is inspired by the human brain and mimics the operation of biological neurons. A hierarchical, deep artificial neural network is formed by connecting multiple artificial neurons in a layered fashion. The more hidden layers added to the network, the more "deep" the network will be, the more complex nonlinear relationships that can be modeled. Deep learning is widely used in self-driving cars, face and speech recognition, and healthcare applications. The purpose of this course is to provide students with knowledge of key aspects of deep and machine learning techniques in a practical, easy and fun way. The course provides students with practical hands-on experience in training deep and machine learning models using real-world dataset. This course covers several technique in a practical manner, the projects include but not limited to: (1) Train Deep Learning techniques to perform image classification tasks.(2) Develop prediction models to forecast future events such as future commodity prices using state of the art Facebook Prophet Time series.(3) Develop Natural Language Processing Models to analyze customer reviews and identify spam/ham messages.(4) Develop recommender systems such as Amazon and Netflix movie recommender systems.The course is targeted towards students wanting to gain a fundamental understanding of Deep and machine learning models. Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to any student with basic programming knowledge. Students who enroll in this course will master deep and machine learning models and can directly apply these skills to solve real world challenging problems."
