update lists

html/pythondatascience.html

@@ -33,7 +33,6 @@ Learning</a></li>
 <ul>
 <li><a href="#pytorch">PyTorch</a></li>
 <li><a href="#tensorflow">TensorFlow</a></li>
-<li><a href="#mxnet">MXNet</a></li>
 <li><a href="#jax">JAX</a></li>
 <li><a href="#others">Others</a></li>
 </ul></li>
@@ -332,24 +331,6 @@ Distributed Deep learning with Keras &amp; Spark.
 quantization deep learning library.
 <img height="20" src="img/keras_big.png" alt="Keras compatible"></li>
 </ul>
-<h3 id="mxnet">MXNet</h3>
-<ul>
-<li><a href="https://github.com/apache/incubator-mxnet">MXNet</a> -
-Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with
-Dynamic, Mutation-aware Dataflow Dep Scheduler.
-<img height="20" src="img/mxnet_big.png" alt="MXNet based"></li>
-<li><a href="https://github.com/gluon-api/gluon-api">Gluon</a> - A
-clear, concise, simple yet powerful and efficient API for deep learning
-(now included in MXNet).
-<img height="20" src="img/mxnet_big.png" alt="MXNet based"></li>
-<li><a href="https://github.com/amzn/xfer">Xfer</a> - Transfer Learning
-library for Deep Neural Networks.
-<img height="20" src="img/mxnet_big.png" alt="MXNet based"></li>
-<li><a href="https://github.com/ROCmSoftwarePlatform/mxnet">MXNet</a> -
-HIP Port of MXNet.
-<img height="20" src="img/mxnet_big.png" alt="MXNet based">
-<img height="20" src="img/amd_big.png" alt="Possible to run on AMD GPU"></li>
-</ul>
 <h3 id="jax">JAX</h3>
 <ul>
 <li><a href="https://github.com/google/jax">JAX</a> - Composable
@@ -402,8 +383,6 @@ powerful Automated Machine Learning python library.</li>
 <li><a href="https://github.com/pytorch/text">torchtext</a> - Data
 loaders and abstractions for text and NLP.
 <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible"></li>
-<li><a href="https://github.com/dmlc/gluon-nlp">gluon-nlp</a> - NLP made
-easy. <img height="20" src="img/mxnet_big.png" alt="MXNet based"></li>
 <li><a href="https://github.com/keras-team/keras-nlp">KerasNLP</a> -
 Modular Natural Language Processing workflows with Keras.
 <img height="20" src="img/keras_big.png" alt="Keras based/compatible"></li>
@@ -460,9 +439,6 @@ href="https://github.com/facebookresearch/pytorch3d">PyTorch3D</a> -
 PyTorch3D is FAIR’s library of reusable components for deep learning
 with 3D data.
 <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible"></li>
-<li><a href="https://github.com/dmlc/gluon-cv">gluon-cv</a> - Provides
-implementations of the state-of-the-art deep learning models in computer
-vision. <img height="20" src="img/mxnet_big.png" alt="MXNet based"></li>
 <li><a href="https://github.com/keras-team/keras-cv">KerasCV</a> -
 Industry-strength Computer Vision workflows with Keras.
 <img height="20" src="img/keras_big.png" alt="MXNet based"></li>
@@ -495,6 +471,9 @@ Library for Language-Vision Intelligence.</li>
 <li><a href="https://github.com/alan-turing-institute/sktime">sktime</a>
 - A unified framework for machine learning with time series.
 <img height="20" src="img/sklearn_big.png" alt="sklearn"></li>
+<li><a
+href="https://github.com/JoaquinAmatRodrigo/skforecast">skforecast</a> -
+Time series forecasting with machine learning models</li>
 <li><a href="https://github.com/unit8co/darts">darts</a> - A python
 library for easy manipulation and forecasting of time series.</li>
 <li><a href="https://github.com/Nixtla/statsforecast">statsforecast</a>
@@ -825,15 +804,17 @@ Visualization Tool for your NeuralNetwork.</li>
 <li><a
 href="https://github.com/lanpa/tensorboard-pytorch">tensorboard-pytorch</a>
 - Tensorboard for PyTorch (and chainer, mxnet, numpy, …).</li>
-<li><a href="https://github.com/awslabs/mxboard">mxboard</a> - Logging
-MXNet data for visualization in TensorBoard.
-<img height="20" src="img/mxnet_big.png" alt="MXNet based"></li>
 </ul>
 <h2 id="genetic-programming">Genetic Programming</h2>
 <ul>
 <li><a href="https://github.com/trevorstephens/gplearn">gplearn</a> -
 Genetic Programming in Python.
 <img height="20" src="img/sklearn_big.png" alt="sklearn"></li>
+<li><a
+href="https://github.com/ahmedfgad/GeneticAlgorithmPython">PyGAD</a> -
+Genetic Algorithm in Python.
+<img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
+<img height="20" src="img/keras_big.png" alt="keras"></li>
 <li><a href="https://github.com/DEAP/deap">DEAP</a> - Distributed
 Evolutionary Algorithms in Python.</li>
 <li><a href="https://github.com/kstaats/karoo_gp">karoo_gp</a> - A
@@ -849,6 +830,10 @@ href="https://github.com/manuel-calzolari/sklearn-genetic">sklearn-genetic</a>
 <p><a name="opt"></a> ## Optimization * <a
 href="https://github.com/optuna/optuna">Optuna</a> - A hyperparameter
 optimization framework. * <a
+href="https://github.com/anyoptimization/pymoo">pymoo</a> -
+Multi-objective Optimization in Python. * <a
+href="https://github.com/CMA-ES/pycma?tab=readme-ov-file">pycma</a> -
+Python implementation of CMA-ES. * <a
 href="https://github.com/HIPS/Spearmint">Spearmint</a> - Bayesian
 optimization. * <a href="https://github.com/pytorch/botorch">BoTorch</a>
 - Bayesian optimization in PyTorch.
@@ -1226,6 +1211,9 @@ Evaluate and monitor ML models from validation to production.</li>
 <li><a href="https://github.com/tensorflow/data-validation">TensorFlow
 Data Validation</a> - Library for exploring and validating machine
 learning data.</li>
+<li><a href="https://github.com/capitalone/datacompy">DataComPy</a>- A
+library to compare Pandas, Polars, and Spark data frames. It provides
+stats and lets users adjust for match accuracy.</li>
 </ul>
 <h2 id="evaluation">Evaluation</h2>
 <ul>
@@ -1331,3 +1319,6 @@ guideline</a>.</p>
 <p>This work is licensed under the Creative Commons Attribution 4.0
 International License - <a
 href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p>
+<p><a
+href="https://github.com/krzjoa/awesome-python-data-science">pythondatascience.md
+Github</a></p>