Class 21 Machine Learning Random Forest in Python
You can find the slides and notebook on my GitHub repository for the course:
https://github.com/PJalgotrader/ML-USU-SP21
Topics covered:
Bagging and random forest in Python
Gridsearch cross validation
Feature importance
Here is a Crash course in machine learning concepts:
https://www.youtube.com/playlist?list=PL2GWo47BFyUPWL5fBZSn6FFHRr1bSkX_J
Here is a detailed course on machine learning and its applications in finance:
https://www.youtube.com/playlist?list=PL2GWo47BFyUM-5XvrQ20DZB4zyzlgwp5A You can find the
Видео Class 21 Machine Learning Random Forest in Python канала Pedram Jahangiry
https://github.com/PJalgotrader/ML-USU-SP21
Topics covered:
Bagging and random forest in Python
Gridsearch cross validation
Feature importance
Here is a Crash course in machine learning concepts:
https://www.youtube.com/playlist?list=PL2GWo47BFyUPWL5fBZSn6FFHRr1bSkX_J
Here is a detailed course on machine learning and its applications in finance:
https://www.youtube.com/playlist?list=PL2GWo47BFyUM-5XvrQ20DZB4zyzlgwp5A You can find the
Видео Class 21 Machine Learning Random Forest in Python канала Pedram Jahangiry
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Module 6- Part 1- Deep Sequence Modeling- what is RNN and why should we go beyond it?Class 13 part 3 VIFClass 17 Machine Learning SVM Regression in PythonPart 17-Logistic regression model in machine learningModule 4- Part 2- Deep Neural Networks Regularization techniquesTime-Series Data prep for ML & DL: Single and Multi-Output Forecasting! (forecasting market returns)Part 12-Polynomial Regression in Machine learningModule 4- Part 1- Deep Neural Networks basicsPart 3-Different types of machine learning algorithmsClass 7 part 2 What is OLSPart 8-Machine learning solvers BEYOND Gradient Descent (SGD, Momentum, Adagrad, Adam)Module 12- Python part1: Mastering Clustering techniques using Sklearn (Kmeans, Hierarchical)Class 6 part 2 Stats review in RModule 5- Part 1- Deep Computer Vision BasicsClass 24 part IV Heteroskedasticity examplesModule 6- Python1- Master Multi-Feature Timeseries Forecasting with LSTM in TensorFlowWelcome to the Deep Forecasting course (Advanced Timeseries with Econometrics, ML and DL)Module 7- Part 1- The Essential Transformers Prerequisites! Why attention is ALL you needClass 12 Machine Learning KNN theory (K Nearest Neighbors part 1 of 2)Part 20-KNN machine learning model for classificationClass 10 Logistic regression