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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practical-neural-networks-deep-learning-in-r/
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课程名称：R语言中的实用神经网络与深度学习 课程概述：这是一门关于神经网络和深度学习的全面课程，旨在帮助学员掌握R语言在数据科学中的应用。通过本课程，您无需再选修其他课程或购买书籍，就能深入学习R语言的数据科学。在大数据时代，全球各地的公司都在利用R语言处理海量信息，掌握神经网络和深度学习将为您的职业发展增添竞争优势。 讲师简介：课程由米娜瓦·辛格（Minerva Singh）授课，她是一位经验丰富的数据科学家，获得牛津大学地理与环境学的硕士学位，并在剑桥大学完成了博士学位。她在分析真实数据和撰写国际期刊论文方面拥有超过五年的经验。 课程内容：本课程涵盖R语言神经网络和深度学习的主要方面，从数据读取和清洗开始，直至实施强大的神经网络和深度学习算法，进行性能评估。您将接触到H2O和MXNET等强大的R语言深度学习包，学习深度神经网络（DNN）、卷积神经网络（CNN）和递归神经网络（RNN）等框架，并将这些框架应用于现实数据（如信用卡欺诈数据、肿瘤数据和图像数据等），用于分类和回归应用。 适合人群：课程无需具备R语言或统计/机器学习的先前知识，讲师将通过简明易懂的实践方法详细讲解R语言中的复杂概念，帮助学员在真实数据上实施所学方法。课程还提供实用的代码和数据，确保学员能在实际工作中运用所学知识。 加入课程：现在就来参加这个课程，获取R语言神经网络与深度学习的全部知识！
YOUR COMPLETE GUIDE TO PRACTICAL NEURAL NETWORKS & DEEP LEARNING IN R: This course covers the main aspects of neural networks and deep learning. If you take this course, you can do away with taking other courses or buying books on R based data science. In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By becoming proficient in neural networks and deep learning in R, you can give your company a competitive edge and boost your career to the next level!LEARN FROM AN EXPERT DATA SCIENTIST:My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University. I have +5 years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journals.Over the course of my research I realized almost all the R data science courses and books out there do not account for the multidimensional nature of the topic. This course will give you a robust grounding in the main aspects of practical neural networks and deep learning. Unlike other R instructors, I dig deep into the data science features of R and give you a one-of-a-kind grounding in data science.You will go all the way from carrying out data reading & cleaning to to finally implementing powerful neural networks and deep learning algorithms and evaluating their performance using R.Among other things:You will be introduced to powerful R-based deep learning packages such as h2o and MXNET. You will be introduced to deep neural networks (DNN), convolution neural networks (CNN) and recurrent neural networks (RNN). You will learn to apply these frameworks to real life data including credit card fraud data, tumor data, images among others for classification and regression applications. With this course, you'll have the keys to the entire R Neural Networks and Deep Learning Kingdom!NO PRIOR R OR STATISTICS/MACHINE LEARNING KNOWLEDGE IS REQUIRED:You'll start by absorbing the most valuable R Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R. My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real-life.After taking this course, you'll easily use data science packages like caret, h2o, mxnet to work with real data in R...You'll even understand the underlying concepts to understand what algorithms and methods are best suited for your data. We will also work with real data and you will have access to all the code and data used in the course. JOIN MY COURSE NOW!
