Data Mining
Comprehensive exploration of data mining techniques, covering preprocessing, association rules, classification methods, and clustering algorithms for extracting valuable insights from datasets.
Project and Production Management
Comprehensive overview of project and production management, covering identification, appraisal, scheduling, resource allocation, monitoring, and organizational aspects, plus production system lifecycle and decision-making tools.
Bank Transaction Fraud Detection with Data Science - Fraud Detection Using Machine Learning
Learn effective data science techniques for detecting bank transaction fraud using machine learning, decision trees, and anomaly detection. Gain practical insights through real-world case studies and hands-on guidance.
Imperfect Information: Information Sets and Sub-game Perfection in Game Theory - Lecture 18
Explore game theory concepts like information sets, imperfect information games, and subgame perfection. Learn to analyze complex strategic interactions and refine equilibrium notions in sequential games.
Gradient Boost
Explore the fundamentals and advanced concepts of Gradient Boost for regression and classification in machine learning.
CART - Classification and Regression Trees
Explore decision and regression trees, from basic concepts to advanced techniques like feature selection, missing data handling, and pruning. Includes practical Python implementation.
Machine Learning
The course places machine learning in its context within AI and gives an introduction to the most important core techniques such as decision tree-based inductive learning, inductive logic programming, reinforcement learning and deep learning through deci…
Programming the Internet - C4 Public Lecture
Explore the evolution of programming for internet-scale applications, addressing challenges in distributed computing, concurrency, and scalability through innovative methodologies and infrastructure changes.
Decision Trees and Ensemble Methods
Explore decision trees, ensemble methods, and advanced techniques like random forests and boosting algorithms for improved machine learning model performance.
Data Mining with Weka
Learn data mining techniques using Weka software. Explore datasets, build classifiers, visualize data, and understand key concepts like cross-validation, overfitting, and ensemble learning.
NeuroTree - A Differentiable Tree Operator for Tabular Data
Explore NeuroTree, a differentiable tree operator for tabular data, addressing traditional tree limitations through simultaneous node learning and built-in ensemble techniques.
CBW's Machine Learning Workshops May 25-26, 2021
Comprehensive workshop on machine learning in bioinformatics, covering decision trees, neural networks, hidden Markov models, and practical applications using Keras and Scikit-Learn.
Ensemble Learning - Decision Tree Algorithm - Gini Index
Master ensemble learning techniques, decision trees, and boosting methods. Hands-on demos with real datasets enhance understanding of these powerful machine learning concepts for improved model performance.
Decision Tree in Data Mining and Machine Learning - Algorithm Tutorial
This 'Decision Tree in Data Mining' video will help you to comprehensively learn all the concepts of decision tree such as Impurity, Gini index, and pruning.
Machine Learning Algorithms
Explore key machine learning algorithms including Linear Regression, Naive Bayes, KNN, SVM, and Random Forest. Learn their practical applications and importance in modern technology.
Marketing & Retail Analytics
Comprehensive tutorial on marketing analytics, covering RFM analysis, clustering, churn prediction, market basket analysis, and CLV modeling using tools like Tableau and KNIME.
Classification with Decision Trees
Learn to implement classification using decision trees in R, covering key concepts like Gini index, entropy, and impurity measurement. Explore advantages, case studies, and various algorithms for effective machine learning applications.
Machine Learning
Comprehensive 7-day exploration of key machine learning algorithms, from regression techniques to clustering methods, enhancing data science skills through live interactive sessions.
Decision Support Systems
Explore decision support systems, from basic concepts to advanced techniques like expert systems and neural networks, enhancing your ability to make informed business choices.
E2EML - How Selected Models and Methods Work
Explore key machine learning algorithms and methods, including decision trees, Bayes Theorem, autocorrelation, Support Vector Machines, and k-nearest neighbors, in this comprehensive video series.
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.