Mastering Recommender Systems
Explore top strategies for building effective e-commerce recommendation systems, featuring insights from Kaggle Grandmasters on candidate generation, reranking, and model ensembling techniques.
Machine Learning
Comprehensive Hindi course covering machine learning fundamentals, algorithms, and practical implementations using Python, with real-world examples and solved problems.
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.
Pattern Recognition
This course provides a fairly comprehensive view of the fundamentals of pattern classification and regression. Topics covered in the lectures include an overview of pattern classification and regression; Bayesian decision making and Bayes classifier
Machine Learning Pipelines
Explore advanced house price prediction through data analysis, feature engineering, and selection techniques for improved model accuracy.
Feature Selection
Learn techniques for effective feature selection in machine learning, including variance threshold, correlation analysis, information gain, and chi-square statistical analysis.
Exploratory Data Analysis
Learn advanced techniques for exploratory data analysis and feature engineering in house price prediction, including automated visualization tools and efficient EDA libraries.
LDA Application in Entertainment Industry
Explore Linear Discriminant Analysis application in entertainment, covering key concepts, data analysis, and practical implementation using Jupyter Notebook for feature selection and classification.
R Tutorials
Comprehensive R tutorials covering bioinformatics, statistics, and data visualization. Learn to analyze gene expression, perform regression, create plots, and conduct survival analysis using R programming.
Data Mining Crash Course
Comprehensive overview of data mining essentials, covering data types, quality, preprocessing, similarity analysis, and visualization techniques for effective data-driven decision making.
EvalML AutoML Library to Automate Feature Engineering, Feature Selection, Model Creation and Tuning
Explore EvalML, an AutoML library automating feature engineering, selection, model creation, and tuning. Learn to streamline your data science workflow and improve project efficiency.
John Harer - Topological Data Analysis and Machine Learning
Explore topological data analysis and machine learning, covering methodology, examples, dimension reduction, and advanced techniques for feature extraction and classification.
Building Your First Machine Learning Model and Model Validation - Day 9
Learn to build and validate your first machine learning model using scikit-learn. Explore techniques for handling large datasets, selecting features, and evaluating model performance through hands-on exercises.
Step-by-Step Machine Learning Project Implementation: EDA, Feature Engineering, Selection, and Model Training
Comprehensive guide to implementing a machine learning project, covering data cleaning, EDA, feature engineering, selection, model training, and hyperparameter tuning.
Know Thy Operator: Behavior-Based Event Detection in Industrial Facilities
Explore industrial process data analysis, machine learning for variability tracing, and behavior-based event detection in facilities. Learn about cluster tuning algorithms and operator response characterization.
Discrete Optimization-Aided Structured Learning at Scale - IPAM at UCLA
Explore discrete optimization techniques for structured learning, featuring algorithmic aspects, statistical setups, and approaches to feature selection and learning trees.
Tools of High Dimensional Data - Lecture 3
Explore high-dimensional data analysis techniques with Bruce Walsh, focusing on advanced tools and methods for complex datasets in biological evolution and genetics.
Making Sense of Your Data: Statistics and Machine Learning - Lecture 2
Explore advanced statistical techniques and machine learning methods for analyzing complex neutrino data, enhancing your ability to extract meaningful insights from experimental results.
Simultaneous Feature Selection and Outlier Detection Using Mixed-Integer Programming
Explore mixed-integer programming for simultaneous feature selection and outlier detection in high-dimensional regressions, with applications to biomedical research and microbiome studies.
Machine Learning Applications in Healthcare - Saudi Arabian Hospital Case Studies
Explore real-world applications of machine learning in Saudi Arabian healthcare through case studies focusing on breast cancer classification and predictive modeling techniques.
Machine Learning Fundamentals - Lecture 6
Dive into advanced machine learning concepts and techniques through comprehensive coverage of key algorithms, theoretical foundations, and practical applications in data science.