Andreas Mueller
1.1만
구독자
51
영상
최근 영상
Sprint Instructions for scikit-learn Vol 2
Scikit-learn sprint instructions
Channel Intro - Applied Machine Learning
Applied ML 2020 - 21 - Time Series and Forecasting
Applied ML 2020 - 20 - Advanced neural networks
Applied ML 2020 - 19 - Keras and Convolutional neural nets
Applied ML 2020 - 18 - Neural Networks
Applied ML 2020 - 17 - Word vectors and document embeddings
Applied ML 2020 - 16 - Topic models for text data
Applied ML 2020 - 15 - Working with Text Data
Applied ML 2020 - 14 - Clustering and Mixture Models
Applied ML 2020 - 13 - Dimensionality reduction
Applied ML 2020 - 12 - AutoML (plus some feature selection)
Applied ML 2020 - 11 - Model Inspection and Feature Selection
Applied ML 2020 - 10 - Calibration, Imbalanced data
Applied ML 2020 - 09 - Model Evaluation and Metrics
Applied ML 2020 - 08 - Gradient Boosting
Applied ML 2020 - 07 - Decision Trees and Random Forests
Applied ML 2020 - 06 - Linear Models for Classification
Applied ML 2020 - 05 - Linear Models for Regression
Applied ML 2020 - 04 - Preprocessing
Applied ML 2020 - 03 Supervised learning and model validation
Applied ML 2020 - 02 Visualization and matplotlib
Applied ML 2020 - 01 Introduction
WiMLDS Sprint Instructions NYC Sprint August 2019
Applied Machine Learning 2019 - Lecture 25 - Recommender Systems (Nicolas Hug)
Applied Machine Learning 2019 - Lecture 24 - Recap and summary
Applied Machine Learning 2019 - Lecture 23 - Basics of Time Series
Applied Machine Learning 2019 - Lecture 22 - Advanced Neural Networks
Applied Machine Learning 2019 - Lecture 21 - Keras and Convolutional Neural Networks