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所在平台: Udemy |
课程主页: https://www.udemy.com/course/complete-ios-machine-learning-masterclass/
课程评论：没有评论
课程名称：完整的iOS机器学习大师班 课程概述： 如果你想学习如何构建专业的、能提升职业发展的移动应用，并利用机器学习将其提升到一个新的水平，这门课程将非常适合你。完整的iOS机器学习大师班™ 是你进行iOS机器学习所需的唯一课程。机器学习是一个快速增长的领域，正在革新许多行业，科技巨头如谷歌和IBM走在前列。在本课程中，你将使用最前沿的iOS机器学习技术栈，为你的移动应用增加智能和光彩。我们正进入一个新纪元，只有被视为“智能”的应用和游戏才能生存。 课程内容： - 掌握应用机器学习的三个基础分支：图像与视频处理、文本分析和语音与语言识别。 - 通过实践教程开发直观的机器学习应用。 - 从零开始创建7个项目，实现代码跟着操作。 - 查找并使用预训练的机器学习模型，并为你的iOS应用做好准备。 - 创建自己的自定义模型，添加图像识别、实时视频流对象识别和Siri语音功能到你的应用中。 - 深入学习关键框架，如CoreML、Vision、CoreGraphics和GamePlayKit。 - 即使没有经验，也能使用Python、Keras、Caffe、TensorFlow、Scikit-learn等工具。 - 提供一年的免费无限主机。 实用案例及真实挑战： 课程中包含多种实用案例和真实世界的挑战，帮助你练习所学内容。告别枯燥、陈腐的课程示例，参与5个真实项目，如图像识别、对象识别以及修改现有训练模型的项目，打造花卉分类应用和灵感来源于硅谷的“Not-Hot Dog”分类器应用。 为何选择iOS机器学习： 机器学习是当今科技领域中最热门的增长领域之一，是增强职业前景和扩展职业工具的重要技能。许多硅谷最热门的公司正在将机器学习融入我们的日常生活。苹果公司自2017年开始在iOS上推广机器学习，使每个人都能够构建智能应用和游戏。 这门课程的独特之处： 机器学习非常广泛且复杂，为了能够有效学习，必须有清晰的全局视角。课程将重点放在不同的实际案例和真实项目上，让学习体验结构化以达到掌握的效果。通过逐行编写代码，你可以清楚地理解每一行代码的含义。课程结束后，你将自信地掌握iOS机器学习的工具和技术。 立即开始，加入机器学习革命的行列，别让自己落在后面！
If you want to learn how to start building professional, career-boosting mobile apps and use Machine Learning to take things to the next level, then this course is for you. The Complete iOS Machine Learning Masterclass™ is the only course that you need for machine learning on iOS. Machine Learning is a fast-growing field that is revolutionizing many industries with tech giants like Google and IBM taking the lead. In this course, you'll use the most cutting-edge iOS Machine Learning technology stacks to add a layer of intelligence and polish to your mobile apps. We're approaching a new era where only apps and games that are considered "smart" will survive. (Remember how Blockbuster went bankrupt when Netflix became a giant?) Jump the curve and adopt this innovative approach; the Complete iOS Machine Learning Masterclass™ will introduce Machine Learning in a way that's both fun and engaging. In this course, you will: Master the 3 fundamental branches of applied Machine Learning: Image & Video Processing, Text Analysis, and Speech & Language RecognitionDevelop an intuitive sense for using Machine Learning in your iOS appsCreate 7 projects from scratch in practical code-along tutorialsFind pre-trained ML models and make them ready to use in your iOS appsCreate your own custom models Add Image Recognition capability to your apps Integrate Live Video Camera Stream Object Recognition to your apps Add Siri Voice speaking feature to your apps Dive deep into key frameworks such as coreML, Vision, CoreGraphics, and GamePlayKit. Use Python, Keras, Caffee, Tensorflow, sci-kit learn, libsvm, Anaconda, and Spyder-even if you have zero experienceGet FREE unlimited hosting for one yearAnd more! This course is also full of practical use cases and real-world challenges that allow you to practice what you're learning. Are you tired of courses based on boring, over-used examples? Yes? Well then, you're in a treat. We'll tackle 5 real-world projects in this course so you can master topics such as image recognition, object recognition, and modifying existing trained ML models. You'll also create an app that classifies flowers and another fun project inspired by Silicon Valley™ Jian Yang's masterpiece: a Not-Hot Dog classifier app! Why Machine Learning on iOSOne of the hottest growing fields in technology today, Machine Learning is an excellent skill to boost your your career prospects and expand your professional tool kit. Many of Silicon Valley's hottest companies are working to make Machine Learning an essential part of our daily lives. Self-driving cars are just around the corner with millions of miles of successful training. IBM's Watson can diagnose patients more effectively than highly-trained physicians. AlphaGo, Google DeepMind's computer, can beat the world master of the game Go, a game where it was thought only human intuition could excel. In 2017, Apple has made Machine Learning available in iOS so that anyone can build smart apps and games for iPhones, iPads, Apple Watches and Apple TVs. Nowadays, apps and games that do not have an ML layer will not be appealing to users. Whether you wish to change careers or create a second stream of income, Machine Learning is a highly lucrative skill that can give you an amazing sense of gratification when you can apply it to your mobile apps and games.Why This Course Is DifferentMachine Learning is very broad and complex; to navigate this maze, you need a clear and global vision of the field. Too many tutorials just bombard you with the theory, math, and coding. In this course, each section focuses on distinct use cases and real projects so that your learning experience is best structured for mastery. This course brings my teaching experience and technical know-how to you. I've taught programming for over 10 years, and I'm also a veteran iOS developer with hands-on experience making top-ranked apps. For each project, we will write up the code line by line to create it from scratch. This way you can follow along and understand exactly what each line means and how to code comes together. Once you go through the hands-on coding exercises, you will see for yourself how much of a game-changing experience this course is.As an educator, I also want you to succeed. I've put together a team of professionals to help you master the material. Whenever you ask a question, you will get a response from my team within 48 hours. No matter how complex your question, we will be there-because we feel a personal responsibility in being fully committed to our students. By the end of the course, you will confidently understand the tools and techniques of Machine Learning for iOS on an instinctive level. Don't be the one to get left behind. Get started today and join millions of people taking part in the Machine Learning revolution. topics: ios swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios12 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios12 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios12 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios12 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios12 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection
