Python vs R for machine learning - Data Science Stack Exchange
Jun 12, 2014 · I'm just starting to develop a machine learning application for academic purposes. I'm currently using R and training myself in it. However, in a lot of places, I have seen people …
python - What do x and y mean when working with data in the …
Dec 14, 2021 · What do x and y mean when working with data in the machine learning domain? Ask Question Asked 4 years, 1 month ago Modified 2 years, 8 months ago
machine learning - How to train ML model with multiple variables ...
Oct 2, 2018 · You can either build say 3 separate models (or 9, if you want all 9 permutations of city vs store), but the more conventional way might be one hot coding your string based …
Best practices to store Python machine learning models
What are the best practices to save, store, and share machine learning models? In Python, we generally store the binary representation of the model, using pickle or joblib.
python - Incremental Learning with sklearn: warm_start, partial_fit ...
Answering my own question after some investigation: warm_start=True and calling .fit() sequentially should not be used for incremental learning on new datasets with potential …
machine learning - How to split data into 3 parts in Python
Feb 4, 2020 · I'm working on a company project which I will need to do data partition into 3 parts - Train, Validation, and Test(holdout). Does anyone know how I can split the data into 3 parts …
Merging two datasets with different features for machine learning ...
Jun 4, 2022 · I'm trying to create a model which predicts Real estate prices with xgboost in machine learning, my question is : Can i combine two datasets to do it ? First dataset : 13 …
machine learning - Open source Anomaly Detection in Python
Jul 23, 2015 · machine-learning python data-mining anomaly-detection library Share Improve this question edited Oct 25, 2020 at 10:07
python - How to apply machine learning model to new dataset
I'm very new to machine learning & python in general and I'm trying to apply a Decision Tree Classifier to my dataset that I'm working on. I would like to use this model to predict the …
Fully-Configured Deep Learning Virtual Machines in Python …
Fully-Configured environment setup for Deep Learning Virtual Machines in Python (VirtualBox or VMware) Often when we start working on any new technology, the most common challenge …