Multi-Way Analysis - The Algorithm
Explore the alternating least squares algorithm for multi-way analysis, focusing on PARAFAC modeling in chemometrics. Learn about notation, potential problems, and alternative approaches.
Understanding Audio Data for Deep Learning
Explore fundamental audio processing concepts for deep learning, including waveforms, pitch, Fourier transform, and MFCCs, essential for AI applications in sound analysis.
Statistical Rethinking 2023 - Fitting Over & Under
Explore advanced statistical concepts including cross-validation, regularization, and robust regression to enhance model fitting and selection techniques in data analysis.
Statistical Rethinking 2022 - Gaussian Processes
Explore Gaussian processes, spatial confounding, and phylogenetic inference in statistical modeling. Learn to apply these concepts to real-world examples like oceanic covariance and primate phylogeny.
Automated Insights in Finance Using Machine Learning & AI
Explore AI and ML techniques for extracting actionable insights from alternative data sources in finance, leading to profitable trading strategies and robust portfolio construction.
Machine Learning for Continuous Integration - Andrea Frittoli & Kyra Wulffert - ODSC Europe 2019
Explore machine learning techniques for analyzing CI/CD pipeline data, extracting insights, and automating failure identification using open-source tools like TensorFlow and Pandas with real-life OpenStack community data.
Price Optimisation - From Exploration to Productionising - David Adey, PhD & Alexey Drozdetskiy, PhD
Explore dynamic price optimization using machine learning, from data analysis to cloud deployment. Learn about feature encoding, model selection, efficiency improvements, and practical implementation strategies for revenue growth.
Towards Deep Learning Models Resistant to Adversarial Attacks
Explore deep learning model vulnerabilities and defense strategies against adversarial attacks, examining research findings and experimental results.
Overly Optimistic Prediction Results on Imbalanced Data - Flaws and Benefits of Over-sampling
Explore flaws and benefits of over-sampling in imbalanced datasets, examining prediction results and comparing studies to improve machine learning model performance.
Counterfactual Evaluation of Machine Learning Models
Explore counterfactual evaluation techniques for machine learning models, focusing on charge outcomes and iterative improvements in financial technology applications.
Fraud Detection in Bitcoin Payment Networks
Explore fraud detection in Bitcoin networks using machine learning, covering techniques like deep learning and entity recognition for effective cryptocurrency security.
Applied Machine Learning for Startups - Arshak Navruzyan
Applied ML strategies for startups: practitioner training, team structures, guidelines, and cutting-edge techniques in NLP and deep learning.
Time Series Forecasting with XGBoost - Advanced Methods
Explore advanced time series forecasting with XGBoost, covering outlier removal, cross-validation, lag features, and future predictions. Enhance your skills in handling complex time-dependent data for improved forecasting accuracy.
Time Series Forecasting with XGBoost - Use Python and Machine Learning to Predict Energy Consumption
Learn to predict energy consumption using XGBoost and Python in this hands-on tutorial. Covers data preparation, feature engineering, model building, and forecasting techniques for time series analysis.
Machine Learning for Beginners - Data Scientists and Analysts
Comprehensive introduction to machine learning for data professionals, covering key concepts, techniques, and practical applications in business contexts, with hands-on coding examples.
Autoencoders Explained Easily
Intuitive explanation of autoencoders, covering key concepts like representation learning and latent space, with applications in data generation, denoising, and anomaly detection.
Recurrent Neural Networks Explained Easily
Explore Recurrent Neural Networks: architecture, time series, and Back Propagation Through Time. Learn about simple RNN units and their applications in sequence processing tasks.
Build a Spotify-Like Music Recommender System in Python
Create a Spotify-like music recommender system using Python, collaborative filtering, and Alternating Least Squares. Learn about music recommendation types, Spotify's architecture, and implement artist suggestions with the 'implicit' library.
Hybrid Classical-Quantum Algorithms
Explore hybrid algorithms combining quantum and classical computing for optimization and inference, leveraging strengths of both platforms to solve complex problems efficiently.
Insights on Gradient-Based Algorithms in High-Dimensional Learning
Explore gradient-based algorithms in high-dimensional learning, covering statistical physics solutions for performance analysis in nonconvex settings like spiked mixed matrix-tensor model, perceptron, and phase retrieval.
Neural Networks and Spurious Correlations
Explore neural networks' vulnerability to spurious correlations and strategies to enhance robustness, including reweighting, subsampling, and overcoming simplicity bias in machine learning models.