Med Post

[philusnarh]

Electricity Consumption https://nbviewer.jupyter.org/github/cs109-energy/cs109-energy.github.io/blob/master/iPython/Exploratory%20Analysis.ipynb https://machinelearningmastery.com/how-to-load-and-explore-household-electricity-usage-data/ https://www.kaggle.com/robikscube/hourly-energy-consumption#COMED_hourly.csv

Sentiment Analysis with Python (Part 1) https://towardsdatascience.com/sentiment-analysis-with-python-part-1-5ce197074184

Time Series 1 https://towardsdatascience.com/an-end-to-end-project-on-time-series-analysis-and-forecasting-with-python-4835e6bf050b

Open Machine Learning Course. Topic 9. Part 1. Time series analysis in Python https://medium.com/open-machine-learning-course/open-machine-learning-course-topic-9-time-series-analysis-in-python-a270cb05e0b3

Stochastic Process http://www.turingfinance.com/random-walks-down-wall-street-stochastic-processes-in-python/

Jason Data sites https://machinelearningmastery.com/time-series-datasets-for-machine-learning/

https://github.com/mubeta06/python/blob/master/signal_processing/sp/ssim.py

moving av https://www.datascience.com/blog/python-anomaly-detection https://www.kaggle.com/kcsener/8-recurrent-neural-network-rnn-tutorial

Having an Imbalanced Dataset? Here Is How You Can Fix It https://towardsdatascience.com/having-an-imbalanced-dataset-here-is-how-you-can-solve-it-1640568947eb

[philusnarh]

ECG

https://www.kaggle.com/pharvesh/cnn-for-ptb-database-99-93 https://www.kaggle.com/durgaprasad64/arima-method-for-forecasting-product-sales https://www.kaggle.com/arthurtok/introduction-to-ensembling-stacking-in-python https://www.kaggle.com/shayanfazeli/heartbeat/kernels http://ecgview.org/download.asp https://www.researchgate.net/post/Where_can_I_find_a_database_for_all_types_of_standard_ECG_and_PCG_signals https://data.mendeley.com/datasets/7dybx7wyfn/3 https://machinelearningmastery.com/time-series-datasets-for-machine-learning/ https://chrisalbon.com/machine_learning/preprocessing_structured_data/detecting_outliers/ https://www.datascience.com/blog/python-anomaly-detection

Gaussian P. https://medium.com/panoramic/gaussian-processes-for-little-data-2501518964e4

Intuitive RF https://medium.com/panoramic/technical-deep-dive-random-forests-7cf4bbc4c11a

[philusnarh]

Overview of feature selection methods https://towardsdatascience.com/overview-of-feature-selection-methods-a2d115c7a8f7

How I built a spreadsheet app with Python to make data science easier https://hackernoon.com/introducing-grid-studio-a-spreadsheet-app-with-python-to-make-data-science-easier-tdup38f7

FC-DenseNet — One Hundred Layers Tiramisu, Fully Convolutional DenseNet https://towardsdatascience.com/review-fc-densenet-one-hundred-layer-tiramisu-semantic-segmentation-22ee3be434d5

A Simple Explanation of the Softmax Function https://victorzhou.com/blog/softmax/

How to Develop an Information Maximizing GAN (InfoGAN) in Keras https://machinelearningmastery.com/how-to-develop-an-information-maximizing-generative-adversarial-network-infogan-in-keras/ https://www.kdnuggets.com/2019/08/video-introduction-generative-adversarial-networks.html

Convolutional Neural Networks: A Python Tutorial Using TensorFlow and Keras https://www.kdnuggets.com/2019/07/convolutional-neural-networks-python-tutorial-tensorflow-keras.html

Keras Callbacks Explained In Three Minutes https://medium.com/towards-artificial-intelligence/keras-callbacks-explained-in-three-minutes-846a43b44a16

Sentiment Analysis: a benchmark https://towardsdatascience.com/sentiment-analysis-a-benchmark-903279cab44a

A ConvNet that works on like, 20 samples: Scatter Wavelets https://towardsdatascience.com/a-convnet-that-works-on-like-20-samples-scatter-wavelets-b2e858f8a385

Autoencoders vs PCA: when to use which https://towardsdatascience.com/autoencoders-vs-pca-when-to-use-which-73de063f5d7

Understanding Multi-Label classification model and accuracy metrics https://medium.com/towards-artificial-intelligence/understanding-multi-label-classification-model-and-accuracy-metrics-1b2a8e2648ca

SCRAPER Web Scraping with Python and BeautifulSoup https://medium.com/incedge/web-scraping-bf2d814cc572

Build Simple Web Scraper Using Python & Selenium https://medium.com/@joonasvenlinen/build-simple-web-scraper-using-python-selenium-f0376b6cc8fa

https://towardsdatascience.com/web-scraping-using-python-libraries-fe3037152ed1

An Introduction to Recurrent Neural Networks for Beginners https://victorzhou.com/blog/intro-to-rnns/

Classification of unbalanced datasets https://towardsdatascience.com/classification-of-unbalanced-datasets-8576e9e366af

A better EDA with Pandas-profiling https://towardsdatascience.com/a-better-eda-with-pandas-profiling-e842a00e1136

An Approach Towards Convolutional Recurrent Neural Networks https://towardsdatascience.com/an-approach-towards-convolutional-recurrent-neural-networks-f54cbeecd4a6

https://towardsdatascience.com/how-to-cluster-in-high-dimensions-4ef693bacc6

How to apply data augmentation to deal with unbalanced datasets in 20 lines of code https://medium.com/analytics-vidhya/how-to-apply-data-augmentation-to-deal-with-unbalanced-datasets-in-20-lines-of-code-ada8521320c9

Machine Learning for Beginners: An Introduction to Neural Networks https://towardsdatascience.com/machine-learning-for-beginners-an-introduction-to-neural-networks-d49f22d238f9

Intro to Bash Scripting https://itnext.io/intro-to-bash-scripting-95c5fbc2dcef

Exponential Smoothing Methods for Time Series Forecasting https://medium.com/better-programming/exponential-smoothing-methods-for-time-series-forecasting-d571005cdf80

Using Deep Learning to Classify Relationship State with DeepConnection https://towardsdatascience.com/using-deep-learning-to-classify-relationship-state-with-deepconnection-227e9124c72

Step-by-Step Tutorial to Build a Video Classification Model in Python https://www.analyticsvidhya.com/blog/2019/09/step-by-step-deep-learning-tutorial-video-classification-python/

Video: Getting Started with Neural Networks in Fraud Detection https://towardsdatascience.com/video-getting-started-with-neural-networks-in-fraud-detection-b17932ea215

Probability Learning IV : The Math Behind Bayes - Towards Data Science https://towardsdatascience.com/probability-learning-iv-the-math-behind-bayes-bfb94ea03dd8

Explore and Visualize a Dataset with Python https://towardsdatascience.com/how-to-explore-and-visualize-a-dataset-with-python-7da5024900ef

A Gentle Introduction to Generative Adversarial Network Loss Functions https://machinelearningmastery.com/generative-adversarial-network-loss-functions/

The Actual Difference Between Statistics and Machine Learning https://towardsdatascience.com/the-actual-difference-between-statistics-and-machine-learning-64b49f07ea3

Detecting stationarity in time series data https://www.kdnuggets.com/2019/08/stationarity-time-series-data.html

Detecting toxic comments with Keras and interpreting the model with ELI5 https://medium.com/@armandj.olivares/detecting-toxic-comments-with-keras-and-interpreting-the-model-with-eli5-dbe734f3e86b

Using Transfer Learning to Detect Malaria Diseases https://medium.com/towards-artificial-intelligence/using-transfer-learning-to-detect-malaria-diseases-3b5305ba889a

What is Exponential Distribution https://medium.com/@aerinykim/what-is-exponential-distribution-7bdd08590e2a

Why do we need Genetic Algorithm? https://medium.com/koderunners/genetic-algorithm-part-1-intuition-fde1b75bd3f9

Probability Learning II: How Bayes’ Theorem is applied in Machine Learning https://towardsdatascience.com/probability-learning-ii-how-bayes-theorem-is-applied-in-machine-learning-bd747a960962

Exploratory data analysis in Python. https://towardsdatascience.com/exploratory-data-analysis-in-python-c9a77dfa39ce

https://www.kaggle.com/c/ieee-fraud-detection/notebooks

Scale, Standardize, or Normalize with Scikit-Learn https://towardsdatascience.com/scale-standardize-or-normalize-with-scikit-learn-6ccc7d176a02

Explaining data science, AI, ML and deep learning to management — a presentation and a script — Part 1 of 3 https://towardsdatascience.com/explaining-data-science-ai-ml-and-deep-learning-to-management-a-presentation-and-a-script-4968491eb1e5

How to Implement Progressive Growing GAN Models in Keras https://machinelearningmastery.com/how-to-implement-progressive-growing-gan-models-in-keras/

How to Prepare Texts, Reviews, Comments, Tweets for Sentiment Analysis with No-Code https://medium.com/fluidtable/how-to-prepare-texts-reviews-comments-tweets-for-sentiment-analysis-with-no-code-275c609e471e

Python Tools for a Beginner Data Scientist https://towardsdatascience.com/python-tools-for-a-beginner-data-scientist-39b3b9a4303a

Introduction to Image Segmentation with K-Means clustering https://www.kdnuggets.com/2019/08/introduction-image-segmentation-k-means-clustering.html

Feature Selection for Building and Improving your Machine Learning Model https://medium.com/analytics-vidhya/feature-selection-for-building-and-improving-your-machine-learning-model-e3a81b79487

Git and Github: A Beginner’s Guide for Complete Newbies https://medium.com/@shivam.ranjanraj.srr/git-and-github-a-beginners-guide-for-complete-newbies-420f55ac3fbe

Forecast KPI: RMSE, MAE, MAPE & Bias https://medium.com/analytics-vidhya/forecast-kpi-rmse-mae-mape-bias-cdc5703d242d

How To Use Data Science For Social Impact https://towardsdatascience.com/how-to-use-data-science-for-social-impact-e9b272b1a4b3

Logistic regression from very scratch in Python https://towardsdatascience.com/logistic-regression-from-very-scratch-ea914961f320

Singular Value Decomposition Example In Python https://towardsdatascience.com/singular-value-decomposition-example-in-python-dab2507d85a0

Bayesian Modeling Airlines Customer Service Twitter Response Time https://towardsdatascience.com/bayesian-modeling-airlines-customer-service-twitter-response-time-74af893f02c0

An Introduction to the Naive-Bayes Algorithm https://towardsdatascience.com/an-introduction-to-the-naive-bayes-algorithm-be3bd692273e

MNIST-GAN: Detailed step by step explanation & implementation in code https://medium.com/intel-student-ambassadors/mnist-gan-detailed-step-by-step-explanation-implementation-in-code-ecc93b22dc60

Understanding Decision Trees for Classification (Python) https://towardsdatascience.com/understanding-decision-trees-for-classification-python-9663d683c952

A Comprehensive guide on handling Missing Values https://medium.com/bycodegarage/a-comprehensive-guide-on-handling-missing-values-b1257a4866d1

How to extract online data using Python https://towardsdatascience.com/how-to-extract-online-data-using-python-8d072f522d86

Cluster Analysis: Create, Visualize and Interpret Customer Segments HDB SCAN https://towardsdatascience.com/cluster-analysis-create-visualize-and-interpret-customer-segments-474e55d00ebb

Introduction to Pandas Workshop https://colab.research.google.com/drive/1AiBGt2kgTtd9_2AZLbkEIO731XTYADFY#scrollTo=eYeOHFpjWX9U

Introduction to Image Segmentation with K-Means clustering https://towardsdatascience.com/introduction-to-image-segmentation-with-k-means-clustering-83fd0a9e2fc3

How to Implement Pix2Pix GAN Models From Scratch With Keras https://machinelearningmastery.com/how-to-implement-pix2pix-gan-models-from-scratch-with-keras/

Neural Networks From Scratch - victorzhou.com https://victorzhou.com/series/neural-networks-from-scratch/

Autoencoders vs PCA: when to use which ? https://towardsdatascience.com/autoencoders-vs-pca-when-to-use-which-73de063f5d7

The Complete Guide to Support Vector Machine (SVM) https://towardsdatascience.com/the-complete-guide-to-support-vector-machine-svm-f1a820d8af0b

Easy Web Scraping with Python BeautifulSoup https://medium.com/@feliciaSWE/easy-web-scraping-with-python-beautifulsoup-afc7191d6432

Simple and multiple linear regression with Python https://towardsdatascience.com/simple-and-multiple-linear-regression-with-python-c9ab422ec29c

Listen to Music through the Ubuntu Terminal https://vitux.com/listen-to-music-through-the-ubuntu-terminal/

In 10 minutes: Web Scraping with Beautiful Soup and Selenium for Data Professionals https://towardsdatascience.com/in-10-minutes-web-scraping-with-beautiful-soup-and-selenium-for-data-professionals-8de169d36319

Rules-of-thumb for building a Neural Network https://towardsdatascience.com/17-rules-of-thumb-for-building-a-neural-network-93356f9930af

Understanding RNNs by Example https://towardsdatascience.com/understanding-rnns-by-example-c8cd52b13059

IEEE-CIS Fraud Detection https://www.kaggle.com/c/ieee-fraud-detection/kernels

Building a Bayesian Logistic Regression with Python and PyMC3 https://towardsdatascience.com/building-a-bayesian-logistic-regression-with-python-and-pymc3-4dd463bbb16

Time Series Decomposition & Prediction in Python https://pythonforfinance.net/2019/07/22/time-series-decomposition-prediction-in-python/amp/

Principal Components of PCA https://towardsdatascience.com/principal-components-of-pca-bea010cc1d33

Validation Methods - Towards Data Science https://towardsdatascience.com/validation-methods-e4eefcbee720

Stock Prediction in Python https://towardsdatascience.com/stock-prediction-in-python-b66555171a2

A Simple Introduction to K-Nearest Neighbors Algorithm https://towardsdatascience.com/a-simple-introduction-to-k-nearest-neighbors-algorithm-b3519ed98e

Understanding Random Forest https://towardsdatascience.com/understanding-random-forest-58381e0602d2

Random Matrix Theory: The Best Classifier for prediction of Drug Binding? https://towardsdatascience.com/random-matrix-theory-the-best-classifier-for-prediction-of-drug-binding-f82613fb48ed

Anomaly detection using Isolation forest – Lambda https://lambda.grofers.com/anomaly-detection-using-isolation-forest-80b3a3d1a9d8

Text Classification in Python https://towardsdatascience.com/text-classification-in-python-dd95d264c802

How to Develop a GAN for Generating Handwritten Digits https://machinelearningmastery.com/how-to-develop-a-generative-adversarial-network-for-an-mnist-handwritten-digits-from-scratch-in-keras/

The Poisson Distribution and Poisson Process Explained https://towardsdatascience.com/the-poisson-distribution-and-poisson-process-explained-4e2cb17d459

Ensemble Models Demystified https://medium.com/@ODSC/ensemble-models-demystified-c871d5ee7793

Introduction to the Architecture of Recurrent Neural Networks (RNNs) https://medium.com/towards-artificial-intelligence/introduction-to-the-architecture-of-recurrent-neural-networks-rnns-a277007984b7

Dealing with Imbalanced Classes in Machine Learning https://towardsdatascience.com/dealing-with-imbalanced-classes-in-machine-learning-d43d6fa19d2

The Basics of Recurrent Neural Networks (RNNs) https://medium.com/towards-artificial-intelligence/whirlwind-tour-of-rnns-a11effb7808f

How do I shut down or reboot from a terminal? https://askubuntu.com/questions/187071/how-do-i-shut-down-or-reboot-from-a-terminal

[philusnarh]

PCA/ TSNE https://www.kaggle.com/sulianova/normalization-logistic-regression-random-forest/notebook

Unsupervised learning https://www.kaggle.com/farhanmd29/unsupervised-learning https://www.kaggle.com/sashr07/unsupervised-learning-tutorial https://towardsdatascience.com/a-complete-guide-to-principal-component-analysis-pca-in-machine-learning-664f34fc3e5a https://www.kaggle.com/samratp/creating-customer-segments-unsupervised-learning

Computer Vision https://towardsdatascience.com/computer-vision-for-beginners-part-1-7cca775f58ef

Supervised learning https://alfurka.github.io/2018-11-18-grid-search/ https://medium.com/greyatom/logistic-regression-89e496433063 https://medium.com/@anishsingh20/logistic-regression-in-python-423c8d32838b https://www.kaggle.com/joparga3/2-tuning-parameters-for-logistic-regression https://www.kaggle.com/neisha/heart-disease-prediction-using-logistic-regression https://www.kaggle.com/parthsuresh/binary-classifier-using-keras-97-98-accuracy https://www.pythoninformer.com/python-libraries/matplotlib/line-plots/

Redshift https://www.cv.nrao.edu/course/astr534/MolecularSpectra.html