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所在平台: Udemy |
课程主页: https://www.udemy.com/course/artificial-intelligence-bootcamp-in-r/
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课程名称：R编程中的人工智能训练营 课程概述：这是一门全面的人工神经网络及深度学习的指南，为学习R语言的数据科学提供了完整的解决方案。在大数据时代，全球各地的公司利用R语言来处理海量信息。通过掌握R中的神经网络和深度学习技能，您能够为公司获得竞争优势并提升职业生涯。 课程讲师：Minerva Singh拥有牛津大学地理与环境硕士学位，并在剑桥大学完成博士学位，拥有超过五年的数据科学领域实际数据分析经验，并发表多篇国际同行评审期刊论文。课程强调R数据科学的多维特性，为学员提供扎实的实用神经网络和深度学习基础。 课程内容：课程将带您从数据读取与清理开始，逐步深入到实现强大的神经网络和深度学习算法，并评估其性能。您将学习R语言中的强大深度学习包，如h2o和MXNET，包括深入了解深度神经网络（DNN）、卷积神经网络（CNN）以及无监督学习方法。您还将掌握如何使用Keras框架在图像数据上实现卷积神经网络，并将这些框架应用于实际数据，如信用卡欺诈数据、肿瘤数据和图像数据，用于分类和回归应用。 总之，这门课程将为您开启R语言神经网络与深度学习的全面世界。
YOUR COMPLETE GUIDE TO ARTIFICIAL 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 unsupervised methods. You will learn how to implement convolutional neural networks (CNN)s on imagery data using the Keras frameworkYou 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!
