A General Purpose Machine Learning Library for Python
Project description
PyDojoML
A General Purpose Machine Learning Library for Python
A quick taste of PyDojoML
How to install
You can easily install it with pip
.
Copy-paste this in your terminal and run it.
pip install pydojoml
Good job, now it's time we rock-and-roll!
Simple Linear Regression example:
import numpy as np
from dojo.linear import LinearRegression
# Let's create some data to fit the model to.
X = np.random.randn(100_000, 100)
y = X @ np.random.rand(100)
# Building the model.
linear_reg = LinearRegression()
# Fitting the model is as easy as a call of a method.
linear_reg.fit(X, y)
# Now lets predict.
prediction = linear_reg.predict(X[:20, :])
Dojo's ingredients
Linear Models
- Linear Regression
- LASSO
- Ridge
- Logistic Regression
Deep Neural Networks
- Layers:
- Dense
- Activation
Activation functions
- Linear
- Sigmoid
- Softmax
- TanH
- ReLU
- Leaky ReLU
Losses
- Squared Error
- Cross Entropy
Optimizers
- Stochastic/Batch/Mini-batch Gradient Descent
- Momentum
- RMSprop
- Adam
Regularizer
- L1
- L2
Tree Models
- Classification And Regression Trees (CARTs)
- Extra-Trees
Support Vector Machines
- C-SVM
- Epsilon-SVM
- Nu-SVMs
Bayes
- Naive Bayes algorithm
Ensemble Learning
- AdaBoost
- Model Stacking
Clustering
- Hierarchical Clustering
- K-Means algorithm
Anomaly detection
- Univariate and Multivariate Gaussian Distribution
Dimensionality Reduction Techniques
- Principal Component Analysis
- Linear Discriminant Analysis
Preprocessing
- Encoders:
- Label Encoder
- OneHot Encoder
- Scalers:
- Normalizer
Various metrics
- classification
- regression
- clustering
Model evaluation utils
- Train-Test splits
- K-Fold Cross Validation
Plotting
- Decision Boundary plotter
Data Preprocessing utils
- encoders
- normalizers
- scalers
Natural Language Processing utils
- TF-IDF
Recommender Systems
- Content Based
- Collaborative Filtering
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
PyDojoML-0.4.1.tar.gz
(206.0 kB
view hashes)
Built Distribution
PyDojoML-0.4.1-py3-none-any.whl
(230.5 kB
view hashes)