Example: stock market
Machine Learning 2020 - 國立臺灣大學
Orientation •Focus on deep learning •This course can be your first ML course. •Little overlap with Hsuan-Tien Lin’s (林軒田) Machine Learning Foundations and Machine Learning Techniques. •Include the latest technologies This course
Information
Domain:
Source:
Link to this page:
Documents from same domain
Introduction of Reinforcement Learning - 國立臺灣大學
speech.ee.ntu.edu.twScenario of Reinforcement Learning Agent Environment Observation Action Don’t do Reward that State Change the environment
Self-supervised Learning
speech.ee.ntu.edu.tw•Corpus of Linguistic Acceptability (CoLA) •Stanford Sentiment Treebank (SST-2) •Microsoft Research Paraphrase Corpus (MRPC) •Quora Question Pairs (QQP) ... Sentiment analysis Random initialization Init by pre-train This is the model to be learned. this is good
Convolutional Neural Network - 國立臺灣大學
speech.ee.ntu.edu.twFully Connected Feedforward network output. ... object detection and semantic segmentation”, CVPR, 2014. Convolution Max Pooling Convolution Max Pooling input 25 3x3 filters 50 3x3 ... “Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps”, ICLR, 2014 | ...
Transformer
speech.ee.ntu.edu.twBeam Search A B A B A B A B A B A B A B 0.4 0.9 0.9 0.6 0.4 0.4 0.6 0.6 The green path is the best one. Not possible to check all the paths … Assume there are only two tokens (V=2). The red path is Greedy Decoding. →Beam Search
Machine Learning PyTorch Tutorial - 國立臺灣大學
speech.ee.ntu.edu.twPyTorch Tutorial TA：張恆瑞 (Heng-Jui Chang) 2021.03.05. Outline Prerequisites What is PyTorch? PyTorch v.s. TensorFlow Overview of the DNN Training Procedure ... C++, JavaScript, Swift Debug Easier Difficult (easier in 2.0) Application Research Production. Overview of the DNN Training Procedure Define Neural Network Loss Function Optimizer ...
Convolutional Neural Network - 國立臺灣大學
speech.ee.ntu.edu.twConvolutional Neural Network (CNN) Network Architecture designed for Image 1. Image Classification Model ... Benefit of Convolutional Layer Fully Connected Layer •Some patterns are much smaller than the whole image. Receptive Field …
AUTO-ENCODER
speech.ee.ntu.edu.twVincent, Pascal, et al. "Extracting and composing robust features with denoising autoencoders." ICML, 2008. Add noises The idea sounds familiar? ☺ ...
Generation - NTU Speech Processing Laboratory
speech.ee.ntu.edu.twminimize cross entropy = class 1 class 2 Train a binary classifier . Discriminator ... Image Style Transfer Domain Domain ... Unsupervised Conditional Generation . Learning from Unpaired Data Network 70 Domain Domain ...
You can listen to the English version of this course at ...
speech.ee.ntu.edu.tw•Math: Calculus (微積分), Linear algebra (線性代數) and Probability (機率) •Programming •All the assignments have sample codes based on Python. •You need to be able to read and modify the sample codes. This course will not teach Python. •This course will not teach any Python package, except PyTorch. •Only focus on ML.
Hung-yi Lee 李宏毅 - 國立臺灣大學
speech.ee.ntu.edu.twVector Set as Input 10ms 25ms 400 sample points (16KHz) 39-dim MFCC 80-dim filter bank output frame 1s →100 frames 4
Related documents
CS224W: Machine Learning with Graphs Jure Leskovec, http ...
web.stanford.edu5 coding assignments using Google Colab, each worth 4% Exam: 35% Course project: 20% Proposal: 20%; Final report: 70%; Poster: 10% Extra credit: Ed participation, PyG/GraphGym code contribution Used if you are on the boundary between grades 9/22/2021 Jure Leskovec, Stanford CS224W: Machine Learning with Graphs 8
ポスターセッション - kosen-sympo.org
kosen-sympo.orgP-066 066 Google Colabを用いた物理用Web教材の開発 藤原滉太 秋田高専 電気・電子・情報系 P-067 067 FSSを搭載した導波管スロットアンテナの設計と試作 船木誠哉 秋田高専専攻科 生産システム工学専攻
Google Colab - Tutorialspoint
www.tutorialspoint.comGoogle Colab 2 If you have used Jupyter notebook previously, you would quickly learn to use Google Colab. To be precise, Colab is a free Jupyter notebook environment that runs entirely in the cloud. Most importantly, it does not require a setup and the notebooks that you create