从CFA到如今的Data Science/Deep Learning的学习已经有一年的时间了。期间经历了自我的兴趣、擅长事务的探索和试验,有放弃了的项目,有新开辟的路线,有有始无终的遗憾,也有还在继续的坚持。期间有数不清的弯路、失落,有无法一一道明的挫败和孤独,也有每日重复单调训练而积累起来的自信与欣喜。和朋友聊天让我意识到,将...
然而,Deep Learning也仅仅是Machine Learning的一个细小分支;而Machine Learning中的很多发展、结论以及背后的本质思想,又是和statistics密不可分。过度关注Deep Learning而全然不顾Machine Learning的一些基本事实和其背后的一些statistics的动机,会让你仅仅是知其然,而无法达到知其所以然。更无法使你根据你所要解决的现实...
Today, deep learning is an active area of research, powering some of the most innovative applications in data science. However, deep learning is often seen as a discipline restricted to professionals with PhD-level knowledge of machine learning and mathematics because of its complexity. Fundamentals...
This chapter provides a brief introduction to deep learning, describes some of its advantages and limitations, presents a survey of its many uses in education, and discusses how it may further shape the field of educational data science.
Data Science (AI, Machine Learning, Deep Learning), Blockchain, Big Data, IT Security, Microservices, Philosophy are the fields that are projected to grow by millions of jobs in the near future while eliminating almost 1 Billion jobs. Learn now at LifeCollege.io How do I benefit from Learni...
Machine learning and AI have appeared on the front page of the New York Times three times in recent memory: 1) When a computer beat the world's #1 chess player 2) When Watson beat the world's best Jeopardy players 3) When deep learning algorithms won a chemo-informatics Kaggle competition...
《The Deep Learning Revolution: Rethinking Machine Learning Pipelines》 介绍:深度学习革命. 《The Definitive Guide to Do Data Science for Good》 介绍:数据科学(实践)权威指南. 《Microsoft Academic Graph》 介绍:37G的微软学术图谱数据集. 《Challenges and Opportunities Of Machine Learning In Production》 ...
Deep learning is an aspect of data science that drives many applications and services that improveautomation, performing analytical and physical tasks without human intervention. This enables many everyday products and services—such as digital assistants, voice-enabled TV remotes, credit card fraud dete...
Deep Learning: What Makes It Different? Traditional ML algorithms such as linear or logistic regression, random forest, or gradient boosting use underlying statistical techniques that enable machines to iteratively learn from labeled training data how to perform specific prediction or clustering tasks. Th...
Large data sets is the key here; performant Microsoft’s open-source deep-learning toolkit Ease of use: what, not how Fast Flexible First class on Linux and Windows OpenSource Getting Started with CNTK https://notebooks.azure.com/n/1zbIwzaANic/notebooks/CNTK_101_LogisticRegression.ipynb ...