📝 My Obisidan Notes

        • Assignment 01
      • 01 Abstract Problem
      • 02 High-Level Algorithms and Polynomial Time
      • 03 Degrees of uncertainty
      • 04 Polynomial Time
      • 05 Closure of P under Boolean combinations
      • 06 Nondeterminism by certificates
      • 07 Closure of NP under positive Boolean combination
      • 08 Polynomial-time reductions
      • 09 NP-hardness
      • 10 History of Computing
      • 11 How much harder is solving as compared to just verifying ?
      • 12 P versus NP
      • 13 Hardness for the class NP
      • 14 The first NP-hard problem
      • 15 A Simple reduction - Almost SAT
      • 16 Algorithmic Paradigm to cope with NP-hardness
      • 17 The Stable Matching Problem
      • 18 Stable Matching for allocations within one group
      • 19 What about Stable Matching for allocations between two groups ?
      • 20 How fast can we solve the Stable Matching Problem ?
      • 21 Gale-Shapley Algorithm for STABLE MATCHING
      • 22 What are greedy algorithms ?
      • 23 Dijkstra's Algorithm
      • 24 Minimum Spanning Trees
      • 25 Minimum Spanning Trees via Prim's Algorithm
      • 26 Minimum Spanning Trees via Kruskal's algorithm
      • 27 The Reverse-Delete algorithm for finding MST
      • 28 The Interval Scheduling problem
      • 29 A harder variant of scheduling
      • 30 Greedy algorithm for Partitioning problem
      • 31 What is dynamic programming ?
      • 32 Interval Scheduling problem (without weights)
      • 33 The Weighted Interval Scheduling problem
      • 34 Bellman-Ford Algorithm
      • 35 The Subset Sum Problem
      • 36 Max Independent Set problem on Trees
      • 37 What is divide and conquer ?
      • 38 The MergeSort algorithm
      • 39 Two methods to solve recurrences
      • 40 Counting Number of Inversions
      • 41 How fast can we multiply two n-digit numbers ?
      • 42 Uniform vs No-Uniform models
      • 43 CNF's
      • 44 A first non-uniform class
      • 45 Undecidability
      • 46 Boolean Circuits
      • 47 The EXACT functions
      • 48 A non-symmetric example - Inequality
      • 49 Composing constructions
      • 50 Depth of a circuit
      • 51 Formulas
      • 52 Other gates
      • Algorithms & Complexity
        • Exercise 01
        • Exercise 02
      • 01 Uncertainty
      • 02 Bayesian Estimation
      • 03 Maximum A Posteriori Estimation
      • 04 Maximum Likelihood estimation - Frequentist Framework
      • 05 Bernoulli Distribution
      • 06 Binomial Distribution
      • 07 Poisson Distribution
      • 08 PDF vs PMF
      • 09 Urn Problem
      • 10 Likelihood function
      • 11 Maximum Likelihood Estimate and Estimator
      • 12 The First-Order Optimality Condition
      • 13 Gradient Descent
      • 14 Logistic Regression
      • 15 Maximum Likelihood Estimation of Logistic Regression
      • 16 Cost Function for Logistic Regression
      • 17 Main Assumptions in Logistic Regression
      • 18 Bayes rule as a classifier
      • 19 The Naive Bayes Classifier
      • 20 Information Theory
      • 21 Self Information
      • 22 Entropy
      • 23 Joint Entropy and Conditional Entropy
      • 24 Relative Entropy (Kullback-Leibler Divergence)
      • 25 Cross Entropy
      • 26 Mutual Information
      • 27 Decision Tree
      • 28 Gini Index
      • 29 Model Definition
      • 30 Preparation for Test Set Bounds
      • 31 Test Set Bound (Theorem)
      • 32 Training Set Bounds
      • 33 Occam's Razor Bound
      • 34 Estimator
      • 35 Bias, Variance and Noise
      • 36 Bias-Variance Trade-off
      • 37 Overfitting vs Underfitting
      • 38 Regularisation
      • 39 Bootstrapping ensembles
      • 40 Probabilistic Graphical Model
      • 41 Bayesian Networks
      • 42 Formal Meaning of a Bayesian Network
      • 43 Probabilistic Relationships (Standard Structures)
      • 44 Bayesian Network Inference
      • 45 Marginalisation
      • 46 State Space Graph and Search Tree
      • 47 Generic tree search
      • 48 Constraint Satisfaction Problem
      • 49 Minesweeper as a CSP
      • 50 Variety of CSPs
      • 51 Solving CSPs by standard search formulation
      • 52 Tree Search vs Local Search
      • 53 Local Search for CSPs
      • 54 Optimisation
      • 55 Game is a search problem
      • 56 Minimax
      • 57 Game Tree Pruning
      • AI2
      • 01 Intelligent Data-Driven Bug Report Analysis
      • 02 Intelligent Configuration Performance Learning
      • 03 Intelligent Software Defect Prediction
      • 04 Intelligent Software Testing
      • 05 Software Engineering for AI - System Level Perspectives
      • 06 Intelligent Software Configuration Tuning
      • 07 Evaluation in Intelligent Software Engineering
      • 08 Requirements Engineering for AI-Enabled Systems
      • 09 Software Architecture for AI Systems
      • Intelligent Software Engineering
      • 01 Supervised Learning
      • 02 Optimisation in Logistic Regression
      • 03 Nonlinear Transformation in Machine Learning
      • 04 Support Vector Machines
      • 05 Lagrange Duality and SVM Dual Formulation
      • 06 Support Vector Machines - Dual Predictions & Kernels
      • 07 Soft Margin SVM - Primal and Dual Formulations
      • 08 Sequential Minimal Optimisation (SMO)
      • 09 Linear Regression
      • 10 Bayesian Inference and Probabilistic Linear Regression
      • 11 Bayesian Linear Regression
      • 12 Learning Feasibility
      • 13 VC Dimension and Generalisation
      • 14 Bias and Variance Analysis
      • 15 Overfitting and Regression Model Evaluation
      • 16 Regularisation
      • 17 Validation
      • Machine Learning
        • 01 What is Neural Computation ?
        • 02 Neurons
        • 03 Perceptron Classifier
        • 04 Perceptron Regressor
        • 05 Optimisation Problem
        • 06 Maximum Likelihood
        • 07 Gradient Descent
        • 08 Multi-Layer Perceptron (MLP) Architecture
        • 09 Computation Graphs
        • 10 The Back-propagation Algorithm
        • 11 Training and Loss Function
        • 12 Generalisation
        • 13 Training Protocols & Ethics
        • 14 Activation Functions
        • 15 Digital Image Representation and MLP Limitations
        • 16 Convolutional Neural Network
        • 17 CNN Structure 4D Data
        • 18 Training Optimisation and Normalisation
        • 19 Regularisation & Transfer Learning
        • 20 Dense Prediction & UNet Architecture
        • 21 Supervised vs. Unsupervised Learning
        • 22 Auto-Encoders
        • 23 Contrastive Learning and SimCLR
        • 24 Generative Models and GANs
        • 25 Diffusion Models
        • NC
        • 01 von Neumann Architecture
        • 02 The CPU
        • 03 Memory Layout of a C program
        • 04 Composite data types as structures
        • 05 Passing Pointers to a Function
        • 06 File handling in C
        • 07 Command line arguments in C
        • 08 Sockets
        • 09 Concurrency using Threads
        • 10 Thread
        • 11 Synchronization mechanism in pthreads
        • 12 Memory Management
        • 13 Page Replacement Algorithms
        • 14 Thrashing
        • 15 Memory Management in the Linux Kernel
        • 16 Interaction between kernel and user program
        • 17 Linux kernel modes
        • 18 A tour of Linux Kernel
        • 19 Process Concept
        • 20 Context Switching
        • 21 Scheduling
        • 22 CPU Scheduling
        • 23 Scheduling Algorithms
        • 24 Scheduling For Multiprocessor Systems
        • 25 Linux Implementation of Scheduling
        • 26 The Critical-Section Problem
        • 27 Solution Criteria to Critical-Section Problem
        • 28 Synchronisation Hardware
        • 29 Inefficient Spinning
        • 30 Semaphores
        • 31 File System
        • 32 Caching
        • 33 Disk Scheduling Algorithms
        • 34 Device Drivers
        • OSSP
        • 01 Hashing
        • 02 Kerckhoff's Principle
        • 03 One Time Pads
        • 04 Symmetric Cryptography
        • 05 Padding
        • 06 Block Cipher Modes
        • 07 Probabilistic Encryption
        • 08 Counter Mode (CTR)
        • 09 Known Plain Text Attacks
        • 10 Secure Key Exchange
        • 11 Encryption using RSA
        • 12 IP, TCP, DNS
        • 13 Internet Protocol Stack
        • 14 MAC, IP address, DHCP and ARP
        • 15 ARP Spoofing Attach - Traffic Interception
        • 16 Assumption of Modern Internet
        • 17 Attacks
        • 18 Key Establishment Protocol
        • 19 Needham-Schroeder Public Key Protocol
        • 20 Needham-Schroeder-Lowe Public Key Protocol
        • 21 Forward Secrecy
        • 22 Certificates - Verifying Public Keys
        • 23 Full Station-to-Station Protocol
        • 24 Needham-Schroeder Key Establishment Protocol
        • 25 Some Key Establishment Goals
        • 26 The SSL TLS Protocol
        • 27 X.509 Standard for Certificates
        • 28 Internet Protocol Stack with TLS
        • 29 Self-Signed Certificates
        • 30 Diffie-Hellman in TLS
        • 31 VPNs
        • 32 Onion Routing
        • 33 Network vs Local Injection
        • 34 Fixes - In-band vs Out-band
        • 35 Classifying SQL Injections
        • 36 HTTP & HTTP Communication
        • 37 GET vs POST
        • 38 Cookies - State in a Stateless World
        • 39 Session Hijacking
        • 40 Cross-Site Scripting (XSS)
        • 41 XSS Protections
        • 42 Broken Access Control
        • 43 Cross-site Request Forgery (CSRF)
        • 44 Same-Origin Policy
        • 45 Reverse Engineering
        • 46 Binaries
        • 47 x86-64 Architecture Overview
        • 48 Buffer Overflow
        • S&N

    My Obsidian Notes

    Apr 10, 20261 min read

    🤖 Artificial Intelligence 2

    • Overview of AI2 Topics

    🔐 Security and Networks

    • Overview of Security and Networks Topics

    🖥️ Operating System and Systems Programming

    • Overview of OSSP Topics

    ⚙️ Machine Learning

    • Overview of ML Topics

    🧠 Neural Computation

    • Overview of NC Topics

    ⏱️ Algorithms & Complexity

    • Overview of Algorithms & Complexity Topics

    🐞 Intelligent Software Engineering Notes

    • Overview of Intelligent Software Engineering Topics

    Graph View

    • 🤖 Artificial Intelligence 2
    • 🔐 Security and Networks
    • 🖥️ Operating System and Systems Programming
    • ⚙️ Machine Learning
    • 🧠 Neural Computation
    • ⏱️ Algorithms & Complexity
    • 🐞 Intelligent Software Engineering Notes

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