3.1 . Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. Chapter 3 Part 2: Transport Layer 3 3 USER DATAGRAM PROTOCOL (UDP) – 3.2 Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. • The User Datagram Protocol (UDP) is a connectionless, unreliable transport protocol. • It does […]
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Computable Functions Co-hosted by: Yousef Akiba Turing Computability • We learnt about Turing Machines • A function is Turing computable if there is a TM that can compute it • The Turing thesis (Faith): Every intuitively computable function is Turing computable Gödel’s approach • Recall that Gödel started with initial functions • Zero function (z),
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NP No Problem! Definition 1 • 𝑁𝑃 = {𝐿: 𝐿 decidable by a polynomial time nondeterministic TM} )𝑘𝑛(𝐸𝑀𝐼𝑇𝑁N∈𝑘ڂ =𝑃𝑁• = 𝑛𝑓𝐸𝑀𝐼𝑇𝑁• {𝐿: 𝐿 is a language decidable by an 𝑂 𝑓 𝑛 nondeterministic TM} 𝑃𝑁 ⊆ 𝑃 •  Running Time for nondeterministic TMs • is the maximum number of steps the TM uses on
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PATH • Given a directed graph G and two nodes 𝑠, 𝑡 in 𝐺. Question: Isthereapathfromstot? • 𝑃𝐴𝑇𝐻 = { 𝐺,𝑠,𝑡 :𝐺isadirectedgraphthathasadirectedpathfrom𝑠to𝑡} Is 𝐺,𝑠,𝑡 ∈𝑃𝐴𝑇𝐻? • This is a stronger question than the first one. It hides more questions: Is 𝐺 𝑎 directed graph? Are 𝑠, 𝑡 vertices in 𝐺? Theorem: PATH ∈ 𝑃 •
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2.1 . Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. Chapter 2 Application Layer Chapter 2: Outline 2.2 Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 2.1 INTRODUCTION 2.2 CLIENT-SERVER PARADIGM 2.3 STANDARDAPPLICATIONS 2.4 PEER-TO-PEER PARADIGM 2.5 SOCKET-INTERFACE PROGRAMMING Chapter 2: Objective 2.3 Copyright © The McGraw-Hill
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What is Text Classification Statistical Classification with NLTK and Scikit-Learn Advice on Machine Learning COMP3220 — Document Processing and the Semantic Web Week 03 Lecture 1: Introduction to Text Classification Diego Moll ́a Department of Computer Science Macquarie University COMP3220 2021H1 Diego Moll ́a W03L1: Text Classification 1/32 What is Text Classification Statistical Classification with
Deep Learning Classification in Keras COMP3220 — Document Processing and the Semantic Web Week 04 Lecture 1: Deep Learning for Text Classification Diego Moll ́a Department of Computer Science Macquarie University COMP3220 2021H1 Diego Moll ́a W04L1: Deep Learning 1/23 Deep Learning Classification in Keras Programme 1 Deep Learning 2 Classification in Keras Reading Deep
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W05L1-1-WordEmbeddings Using word embeddings¶ This notebook is based on the code samples found in Chapter 6, Section 1 of Deep Learning with Python and hosted on https://github.com/fchollet/deep-learning-with-python-notebooks. Note that the original text features far more content, in particular further explanations and figures. In [1]: import tensorflow as tf tf.config.experimental.list_physical_devices() Out[1]: [PhysicalDevice(name=’/physical_device:CPU:0′, device_type=’CPU’), PhysicalDevice(name=’/physical_device:XLA_CPU:0′, device_type=’XLA_CPU’), PhysicalDevice(name=’/physical_device:GPU:0′, device_type=’GPU’),
Information Retrieval Evaluation Indexing and Retrieval COMP3220 — Document Processing and the Semantic Web Week 02 Lecture 1: Searching for Information Diego Moll ́a Department of Computer Science Macquarie University COMP3220 2021H1 Diego Moll ́a W02L1: Search 1/53 Information Retrieval Evaluation Indexing and Retrieval Programme 1 Information Retrieval 2 Evaluation Precision and Recall 3 Indexing
Using word embeddings¶ This notebook is based on the code samples found in Chapter 6, Section 1 of Deep Learning with Python and hosted on https://github.com/fchollet/deep-learning-with-python-notebooks. Note that the original text features far more content, in particular further explanations and figures. In [1]: import tensorflow as tf tf.config.experimental.list_physical_devices() Out[1]: [PhysicalDevice(name=’/physical_device:CPU:0′, device_type=’CPU’), PhysicalDevice(name=’/physical_device:XLA_CPU:0′, device_type=’XLA_CPU’), PhysicalDevice(name=’/physical_device:GPU:0′, device_type=’GPU’), PhysicalDevice(name=’/physical_device:XLA_GPU:0′,