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C++- Multithreading and Socket Programming
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C++ Concurrency in Action
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C++- Multithreading and Socket Programming
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Chapter 1 - What is Deep Learning
Chapter 1 - What is Deep Learning
Chapter 2 - The mathematical building blocks of neural networks
Chapter 2 - The mathematical building blocks of neural networks
Chapter 3- Basic Models
Chapter 3- Basic Models
Chapter 4- Getting started with NN- Classification and Regression
Chapter 4- Getting started with NN- Classification and Regression
Chapter 5- Fundamentals of Machine Learning
Chapter 5- Fundamentals of Machine Learning
Chapter 7- Working with keras — a deep dive
Chapter 7- Working with keras — a deep dive
Chapter 8- Introduction to deep learning for computer vision
Chapter 8- Introduction to deep learning for computer vision
Chapter 8- Part II
Chapter 8- Part II
Chapter 9- Advanced Deep Learning for Computer Vision
Equivariance + Invariance
Equivariance + Invariance
Chapter 9- Advanced Deep Learning for Computer Vision
Chapter 10- Deep learning for time-series
Chapter 10- Deep learning for time-series
Multi-Modal Deep Learning Model
Multi-Modal Deep Learning Model
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Section 1
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1765. Map of Highest Peak
1765. Map of Highest Peak
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Future and Completable Future
Future and Completable Future
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Starting Spring Boot Project
Starting Spring Boot Project
ResponseEntity
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SQL + MySQL Notes
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Building Lists and Navigation
Building Lists and Navigation
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Creating and Combining Views
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bet210
Module 1- Business Processes
Module 1- Business Processes
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Module 2- Business Process Modelling
Module 3- Basic IT Infrastructure
Module 3- Basic IT Infrastructure
Module 4- Computing in the Cloud
Module 4- Computing in the Cloud
bet210
cs240
cs240 - Final Exam Notes
cs240 - Final Exam Notes
cs240 - List of Algorithms
cs240 - List of Algorithms
cs240 - MT Study Notes
cs240 - MT Study Notes
cs240
cs241
CS241 - MT Review Questions
CS241 - MT Review Questions
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Module 2 (AKA Lectures 1 - 8)
Module 2 (AKA Lectures 1 - 8)
cs241
cs246
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Lecture 24
cs251
CS251 - Final Exam Notes
CS251 - Final Exam Notes
Lecture 1
Lecture 1
Lecture 2
Lecture 2
Lecture 3
Lecture 3
cs251
Lecture 4
cs341
Assignment 5
Assignment 5
Question 1
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Lecture 4
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Lecture 5
Lecture 5
Lecture 6
Lecture 6
Lecture 7
Lecture 7
Lecture 8
Lecture 8
Lecture 10- Graph Algorithms 1
Lecture 10- Graph Algorithms 1
Lecture 11- finishing BFS, Starting DFS
Lecture 11- finishing BFS, Starting DFS
Lecture 12- DAG Testing, Topsort, SCC
Lecture 12- DAG Testing, Topsort, SCC
Lecture 13- Minimum Spanning Trees
Lecture 13- Minimum Spanning Trees
Lecture 14- Single Source Shortest Path
Lecture 14- Single Source Shortest Path
Lecture 15- All Pairs Shortest Paths
Lecture 15- All Pairs Shortest Paths
Lecture 16- Max Flow
Lecture 16- Max Flow
Lecture 17- Max Flow 2
Lecture 17- Max Flow 2
Lecture 18- Applications of Max Flow
Lecture 18- Applications of Max Flow
Lecture 19- Complexity Intro & Reductions I
Lecture 19- Complexity Intro & Reductions I
Lecture 20- Reductions II
Lecture 20- Reductions II
Lecture 21- Intractability I
Lecture 21- Intractability I
Lecture 22- NP Completeness
Lecture 22- NP Completeness
A2 - Pseudocode
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cs341
Lecture 9
cs348
Lecture 1
Lecture 1
cs348
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cs350
Assignment Notes
Assignment 1 - Notes
Assignment Notes
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Lecture 1
Lecture 2,3
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Lecture 4
Lecture 4
Lecture 5-6
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Lecture 8
Protection is the responsibility of the application writer (the user)
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Lecture 15- VM Hardware 1
Lecture 15- VM Hardware 1
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Lecture 17- VM OS
Lecture 17- VM OS
Lecture 18
Lecture 18
Lecture 19- VM and File Systems
Lecture 19- VM and File Systems
Lecture 20- File Systems
Lecture 20- File Systems
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Lecture 21- File Systems Continued
Lecture 22- File Systems and Scheduling
Lecture 22- File Systems and Scheduling
Lecture 23- Scheduling
Lecture 23- Scheduling
Lecture 24- I-O
Lecture 24- I-O
cs350
Lecture 14-
MT Notes - Summary
MT Prac Notes
cs480
Chapter 1- Perceptron
Chapter 2- Linear Regression
Chapter 3- Support Vector Machines
Chapter 4- Kernels
Chapter 5- Fully Connected Neural Network
Chapter 6 - Convolutional Neural Networks
Chapter 7 - RNN'S and Transformer Architecture Part 1
Chapter 7 - Transformer Architecture Part 2
Chapter 8 - Graph Neural Networks
Chapter 9 - Decision Trees and Ensemble Methods
stat231
Chapter 1
Chapter 1
q3
q3
R Introduction Tutorial
R Introduction Tutorial
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R Tutorial A1
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Assignment 1
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Lecture 14-
Lecture 14-
Jul 08, 2024
1 min read
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