Application of Classification Algorithms
Explore popular classification algorithms, their comparisons, and real-world applications through a case study on employee promotion prediction using various techniques.
Classification Algorithm in Hindi
वर्गीकरण एल्गोरिदम की व्यापक समझ: लिनियर रिग्रेशन से लेकर सपोर्ट वेक्टर मशीन तक, सैद्धांतिक अवधारणाओं और पायथन में कार्यान्वयन के साथ।
Logistic Regression in Hindi
लॉजिस्टिक रिग्रेशन की मूल अवधारणाओं को समझें, सिग्मॉइड फ़ंक्शन का अध्ययन करें, और पायथन में इसका उपयोग करके वर्गीकरण समस्याओं को हल करना सीखें।
Logistic Regression: Overview and Working - Machine Learning Tutorial
लॉजिस्टिक रिग्रेशन की अवधारणा और कार्यप्रणाली को समझें। यह ट्यूटोरियल मशीन लर्निंग की इस महत्वपूर्ण तकनीक को सरल हिंदी में समझाता है।
Classification Algorithm Tutorial - Machine Learning Tutorial
Comprehensive tutorial on classification algorithms in machine learning, covering techniques for categorizing new observations based on training data. Explores supervised learning methods and practical applications.
Fair Clustering: Notations and Algorithms
Explore fair clustering algorithms and their role in preventing discriminatory outcomes in machine learning applications, focusing on group fairness and equal representation across clusters.
Feature Engineering Importance - Practical Application for Feature Engineering
Explore feature engineering techniques for data analysis and classification, including practical application to supermarket sales data. Learn to select, manipulate, and transform features for improved model performance.
Machine Learning and Neural Networks: Logistic Regression - Day 6
Explore logistic regression in machine learning and neural networks, covering key concepts and applications for binary classification problems.
Machine Learning in Cybersecurity - Boon or Boondoggle
Explore machine learning's impact on cybersecurity with Dr. Zulfikar Ramzan. Learn about supervised and unsupervised learning, challenges, and applications in DevOps while gaining insights from a leading industry expert.
Using EEG and Machine Learning to Perform Lie Detection - YOW! 2017
Explore EEG-based lie detection using Azure Machine Learning. Learn about data collection, model building, and limitations in this innovative experiment combining neuroscience and AI.
Obfuscation Classification via Machine Learning for JavaScript, Python, and PHP
Explore machine learning techniques for classifying obfuscated code across JavaScript, Python, and PHP, enhancing cybersecurity analysis and threat detection capabilities.
Repurposing Vulnerability Tickets to Predict Severity Levels - An Introduction to Natural Language Processing and Classification Algorithms
Explore natural language processing and classification algorithms to predict vulnerability severity levels using ticket data, enhancing cybersecurity decision-making and resource allocation.
Fair Classification with Group-Dependent Label Noise
Explore group-dependent label noise in fair classification, addressing challenges and proposing solutions for improved algorithmic fairness in machine learning models.
MLSec Going Deeper
Explore advanced machine learning security concepts, including adversarial samples, attack strategies, and defensive techniques for various ML models.
VFP - A Virtual Switch Platform for Host SDN in the Public Cloud
Explore Microsoft Azure's Virtual Filtering Platform (VFP), a programmable virtual switch for host SDN in public clouds. Learn its design, API, flow language, and real-world performance in large-scale deployments.
Comparison of Papers by Native and Non-Native English Speakers in Physics
Explore linguistic differences in physics papers by native and non-native English speakers, achieving 84% classification accuracy and enhancing scientific communication.
K-Nearest Neighbors Implementation in R
Implement K-Nearest Neighbors algorithm in R programming language. Learn practical application of this machine learning technique for classification and regression tasks.
Logistic Regression: Introduction to Binary Classification and Linear Classifiers
Master logistic regression for binary classification, covering linear classifiers, sigmoid functions, parameter estimation, and log-likelihood functions.
Decision Trees in Neuro-Symbolic AI
Master decision tree algorithms for effective data classification and prediction in machine learning applications.
Predicting Classifier Accuracy in the Wild - Lecture 39
Dive into advanced machine learning concepts with Prof. Sebastiani as he explores methods for predicting classifier accuracy in real-world applications and deployment scenarios.
The Perceptron Algorithm for Linear Classification - Lecture 26
Dive into the Perceptron Algorithm for linear classification, exploring perfect classifiers, margin concepts, and max-margin classifiers while understanding their practical applications.