/Machine_Learning_Collections

Testing repository for various machine learning algorithms and methods using public test data sets

Primary LanguageJupyter Notebook

Machine Learning Algorithm/Coding Test Repository

Sample test data are published at UCI.

Python Packages to install

  • Some nice list of Python packages for Python coding. Another its link is here.
  • Standard Python packages include pandas, numpy, scipy, matplotlib, scikit-learn, seaborn
  • H2O for R and Python
    • The programs run on Java SDK.
    • For Python version, check out the installation instruction here. Basic introduction to its useage is here. If there is a conflict between Linux OS system pip and Anaconda's pip, and you wish to install it on Anaconda envrionment, then use /root/anaconda/bin/pip *** instead of pip install ***
    • Some of its powerful tools are Deep Learning and GBM. Its deep learning so far primarily focuses on the model of multi-layer, feedforward neural networks for predictive modeling.
  • Other useful packages include
    • seaborn for data visualization.
    • Orange for graphic modeling instead of source coding.
    • Theano for deep learning and tensor calculation.
    • numba for JIT (just-in-time compilation) when it involves (especially looping) many generic Python codes and numpy.

List of Files/Folders

README.md
Two Sigma -- Using News to Predict Stock Movements
LSTM-Neural-Network-for-Time-Series-Prediction
hitchhiker-s-guide-to-nlp-in-spacy.ipynb
Sentiment Analysis with Variable length sequences in Pytorch_files
Sentiment Analysis with Variable length sequences in Pytorch.html
Book -- Hands-On Markov Models with Python
Book -- Practical Machine Learning with Python
Spark_for_Telecom_ver2
human_activity_lstm_pytorch_sample.py
human_activity_lstm_pytorch_one_pred_per_timeseries_sample.py
human_activity_keras_CNN_pytorch_one_pred_per_timeseries_sample.py
Distributed_Deep_Learning_on_Spark_Demo
Named_Entity_Recognition_in_News_BidirectionalLSTM-CNN-CoNLL
Pytorch-RNN-text-classification
Deep-Learning-Boot-Camp-2017
Classifying text with TensorFlow Estimators.ipynb
xgboost_cross_validate_pipeline.R
pytorch_sequence_LSTM_models_tutorial.py
pytorch_sequence_LSTM_models_tutorial.ipynb
human_activity_recognition_by_TensorFlow.ipynb
Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras.ipynb
Spark_for_Telecom_Samples_CDSW
Named_Entity_Recognition_in_News_BidirectionalLSTM-CNN-CoNLL_ver2
sentence-classification-pytorch
Book -- Agile_Data_Code_2
Keras-WTT-RNN Engine failure.ipynb
sensor-fusion
practical-data-science-with-hadoop-and-spark
openpayments.ipynb
mltools-pool-detection-by_CNN
handson-ml-ipynb
deep-learning-with-python-notebooks
cheatsheets-ai-png
Solar_Panel_Detection_CNN
Oxford Deep NLP 2017 course_pdf
Deep-Learning-with-Keras
Deep Reinforcement Learning Lecture
Compositional-Attention-Networks-for-Machine-Reasoning-PyTorch
data-science-ipython-notebooks
Time Series Classification Benchmark with LSTM VGG ResNet
Deep Time-to-Failure Network
Basketball_Stats_CDSW_Spark
Deep-Learning-Boot-Camp
MIT_Vadim Smolyakov_Dirichlet Process K-Means Sample
MIT_Vadim Smolyakov_Kaggle Sample
EasyOverHard_SVM
WTTE-RNN-Hackless-churn-modeling
MIT_Vadim Smolyakov_Experiment with Python_Machine Learning Finance Computer Vision
MIT_Vadim Smolyakov_Deep Learning Sample
MIT_Vadim Smolyakov_Computer Vision Sample
Active Thermography and Data Driven Methods_Keras
Intro_to_Spark_by_Cloudera_Data_Science_Workbench
urban-data-science-geospatial
Variational-Autoencoder-PyTorch
crime_analysis_by_Shinny
machine-learning-mindmap
lending_club_data_EDA.ipynb
MIT_Vadim Smolyakov_Algorithmic Trading
Demo Weibull Time-to-event Recurrent Neural Network in Keras
MIT_Vadim Smolyakov_pyspark Sample
LSTM-Human-Activity-Recognition
Kalman-Application
Accelerometer-Explore.ipynb
Extract Gravity Signal.ipynb
DeepOSM-master
Microsoft_GeoLife
Kaggle_Challenges
Computing the optimal road trip across the US.ipynb
classification_of_20_newsgroup_sparse_features.py
plot_xgb_Booster_partial_dependency.R
Approaching Any Machine Learning Problem _ Abhishek Thakur _ No Free Hunch.pdf
Partial Dependence Plots - R Package mlr tutorial.pdf
Kaggle_Nile_Virus_Prediction_byKeras.py
MIT_Vadim Smolyakov_Network Analysis
MIT_Vadim Smolyakov_Machine Learning_Sample
BigData BDTC 2015_全体大会
Mobile User Demographics_xgboost
ODSC_2016
glmnet_Poisson_sample.R
MIT_Vadim Smolyakov_Statistical Learning with R
pyLightGBM_Source_Codes
Ultrasound-Nerve-Segmentation
BossSensor_using_Keras
An Introduction to Supervised Learning via Scikit Learn.pdf
Deep_Learning_from_Others
CNN_MNIST_by_TensorFlow.py
Parcel_to_Coastline_Distance.R
GLM_metrics evaluation_2.R
GLM_metrics evaluation_1.R
Glmnet_Vignette.pdf
glmnet_source_codes_with_sample_data.zip
simple_text_mining_samples
DBN_for_OCR.py
H2O_Day_Ahead_Regression.py
h2o-training-2015
H2O_for_OCR.py
convolution_neural_network_for_OCR.py
test_data
H2O_Day_Ahead_Regression_GBM.R
convolution_neural_network_on_Spark_for_OCR.py