python deep learning notebooks. Open the juptyer projects in a new window to avoid the "something is wrong" error loading from github.
- electricity pricing using a bayesian classifier.
https://github.com/dnishimoto/python-deep-learning/blob/master/Bayesian%20Electricity%20Prices.ipynb
- oil well rock formation type identification using a support vector machine
https://github.com/dnishimoto/python-deep-learning/blob/master/SVM%20Oil%20Facies.ipynb
- deep learning jeep price prediction
*XGBoost regressor to discover the affect of inflation on commodities
*LSTM classifier for predicting accumulation of the Lockheed Martin stock
https://github.com/dnishimoto/python-deep-learning/blob/master/LSTM%20Lockheed%20Martin%20LMT.ipynb
*LSTM classifier for prediction remaining life of an aircraft
- Dense layer classifier for predict import car prices based on features
- Dense layer classifier of the equipment failure. tsne for visualizing the errors
- equipment failure analysis: lstm, volt, pressure, rotation
- market basket analysis: support, conviction, leverage, confidence, lift
- abalone age prediction with 9 features lstm
https://github.com/dnishimoto/python-deep-learning/blob/master/Abalone%20Age%20Prediction.ipynb
- nets group classification using lstm with a confusion matrix for measuring performance
- Curve fitting the dividend earnings of AllState
https://github.com/dnishimoto/python-deep-learning/blob/master/Allstate%20dividends.ipynb
- Dense layer network multiple input and output disease prediction
- Dense layer network to predict concatenated sin segments
- ECG dense layer predictor
https://github.com/dnishimoto/python-deep-learning/blob/master/ECG%20LSTM%20Prediction.ipynb
- Bidirectional lstm classifier for equinex - risk management
https://github.com/dnishimoto/python-deep-learning/blob/master/Equinix%20data%20center.ipynb
- Extraspace vs rio
https://github.com/dnishimoto/python-deep-learning/blob/master/RIO%20vs%20BHP%20Uranium.ipynb
- Duke Energy portfolio strategy
https://github.com/dnishimoto/python-deep-learning/blob/master/Duke%20Energy.ipynb
- LSTM binary classifier
- analysis of apply stock - linear regression
https://github.com/dnishimoto/python-deep-learning/blob/master/stock%20apple%20vs%20vmware.ipynb
- Airline customer satisification - Decision boundary analysis
https://github.com/dnishimoto/python-deep-learning/blob/master/airline%20logistic%20regression.ipynb
- Text summerization with GRU neural machine translation
https://github.com/dnishimoto/python-deep-learning/blob/master/Text%20Summerization%20GRU.ipynb
- Computer vision using Conv2D with Keras
- Shampoo sales using keras conv1d
- I added weight training with random forest for 56 features
- I added deep learn dense network for mnist
https://github.com/dnishimoto/python-deep-learning/blob/master/deep%20learning%20mnist.ipynb
- I added an Text keras lstm network for multi classification labels
- I added multiple variable lstm prediction of bike share
- I added Credit risk of default (logistic regression, xgboost, keras)
https://github.com/dnishimoto/python-deep-learning/blob/master/Credit%20Loan%20Risk%20.ipynb
- I added Electric vehicle trends
https://github.com/dnishimoto/python-deep-learning/blob/master/Electric%20Vehicle%20trends.ipynb
- I added kc housing price prediction using keras network
- I added allstate dividend payments using cumsum
https://github.com/dnishimoto/python-deep-learning/blob/master/Allstate%20dividends.ipynb
- I add meat consumption trends time series analysis
https://github.com/dnishimoto/python-deep-learning/blob/master/Meat%20volume%20timeseries.ipynb
- I added co2 time series analysis
https://github.com/dnishimoto/python-deep-learning/blob/master/CO2%20timeseries%20analysis.ipynb
- I added probability analysis of class room size for different schools in 1938
https://github.com/dnishimoto/python-deep-learning/blob/master/School%20Size%20Probablity.ipynb
- I added Earthquake 5+ analysis
https://github.com/dnishimoto/python-deep-learning/blob/master/Earthquakes%205%20plus.ipynb
- I added Google timeseries analysis
https://github.com/dnishimoto/python-deep-learning/blob/master/Google%20timeseries.ipynb
- I added shampoo sales using rolling window and pytorch conv1d
- I added college admittance for Graduate school using support vector machine
- I added a Happiness and Depression logistic Regression
- I added a Random Forest Classifer for playing tennis based on the weather
https://github.com/dnishimoto/python-deep-learning/blob/master/Random%20Forest%20Tennis.ipynb
- I added Olympic history using heatmap
https://github.com/dnishimoto/python-deep-learning/blob/master/Olympics%20events.ipynb
- I added liver disease analysis using glm
https://github.com/dnishimoto/python-deep-learning/blob/master/Indian%20Liver%20Patient%20.ipynb
- I added crab satelite ~ weight and width ols and glm
- I added Bangladesh well switch using ols and glm
- I added baseball stats using a heatmap to analyze the logistic regression predictions
https://github.com/dnishimoto/python-deep-learning/blob/master/Baseball%20stats.ipynb
- I added an airline comfort rating a logistic regression pipeline
https://github.com/dnishimoto/python-deep-learning/blob/master/Airline%20Comfort%20Ratings.ipynb
- I added a credit card approval using a logistic regression pipeline
- i added face recognition and edge detection using open cv
- I added hyper parameter tuning for credit card default and built a mlpclassifier to predict
- I added candy power ranking using keras linear predictor
https://github.com/dnishimoto/python-deep-learning/blob/master/Candy%20Power%20Ranking.ipynb
- I added credit card default prediction using keras
- I added multinomialnb and kNearestNeighbor UFO sightings predictor
https://github.com/dnishimoto/python-deep-learning/blob/master/UFO%20.ipynb
- I added passenger prediction using LSTM one day back prediction
- I added the pima diabetes dimension reduction
- I added Army AUNR dimensional reduction
- I added Trump tweets
https://github.com/dnishimoto/python-deep-learning/blob/master/Trump%20tweets.ipynb
- I added super bowl prediction creating a probable profile of a winner
https://github.com/dnishimoto/python-deep-learning/blob/master/Superbowel.ipynb
- I added general social survey
https://github.com/dnishimoto/python-deep-learning/blob/master/General%20Social%20Survey.ipynb
- I added baby birthweight predictions
- I added pct change for netflix and domino then feed it into a lstm for a future prediction
*https://github.com/dnishimoto/python-deep-learning/blob/master/LSTM%20Netflix.ipynb
- I added auc the stepwise refinement to find multiple variables for the model using customer churn data
- I added medicare healthcare by drg
- I added linear model of restaurant tips
- I added boise weather for sept 2020, temperature and humidity affected wind speeds
- I added a chicago crime sas file - crime trends from 2001 to 2016 trended down
https://github.com/dnishimoto/python-deep-learning/blob/master/Crime%20analysis%20(SAS).ipynb
- I added a search for the best movies
https://github.com/dnishimoto/python-deep-learning/blob/master/Movies%202013.ipynb
- I added visualization of nitrogen dioxide levels in Utah
- I am hypothesis testing finch beak size changes between 1975 and 2012
I am using python to visualize data and learn from it.
- I added an XGBoost predictor for idaho housing prices
- I added a bayensian predictor for covid cases and deaths (keras)
https://github.com/dnishimoto/python-deep-learning/blob/master/covid%20prediction%20bayesian.ipynb
- I added stackoverflow programmer features
- I added logistic regression telco customer churn prediction
- I added XgBoost classifier for the iris Data. I included the notes to installing xgboost.
https://github.com/dnishimoto/python-deep-learning/blob/master/XGBoost%20Iris.ipynb
- I added Remaining payments (geometric progression)
https://github.com/dnishimoto/python-deep-learning/blob/master/Remaining%20Payment.ipynb
- I added Reinforcement Learning Balancing pole
- I added Reinforcement Learning Tic Tac Toe
- I added Reinforcement Learning NChain
https://github.com/dnishimoto/python-deep-learning/blob/master/Reinforced%20Learning%20NChain.ipynb
- I added LSTM Input_shape (need to fix output)
https://github.com/dnishimoto/python-deep-learning/blob/master/LSTM.ipynb
- I added a logistic regression binary classifier with lasso called (Logistic Regression predicting magazine subscription)
- I added a logistic regression of multiple classes using cross_entropy and softmax called Logistic Regression prediction of Iris.ipynb
- I added a logistic regression binary prediction of whether or not a person will open an account (Logistic Regression open account prediction.ipynb)
- I added a logistic regression binary prediction for credit card fraud
- I added a deep learning stocastic descent to solve a linear matrix X, Y, Z set of equations.
- I added NMF feature reduction to analyze words in a document to build a better search engine using ensemblies
https://github.com/dnishimoto/python-deep-learning/blob/master/NMF%20Search%20Engine.ipynb
https://github.com/dnishimoto/python-deep-learning/blob/master/NMF%20feature%20reduction.ipynb
- I added Michelson vs Newcomb speed of light hypothesis testing code
- I feature analyze and extract using K-means cluster on the Iris classifier using K-means cluster
- I modeled the statistical distribution of the Junk bond market and determine it is not a normal distribution
- I modeled binomal and poisson distributions in python (modeling distributions guassian curves)
https://github.com/dnishimoto/python-deep-learning/blob/master/statistics%20part%201.ipynb
- I built a neural network for predict covid deaths
https://github.com/dnishimoto/python-deep-learning/blob/master/neural%20network.ipynb
- I modeled the trigometric function 5 times sin 1.5 times x plus pi divided 4
- I built a convolution neural net to learn an apple, banana, and orange image (deep learning - cnn - recognizing a list of images)
https://github.com/dnishimoto/python-deep-learning/blob/master/CNN%20%20image%20classification.ipynb
- I built a deep learning network to predict team scores
https://github.com/dnishimoto/python-deep-learning/blob/master/deep%20learning%20addition.ipynb
- I built a deep learning stocastic descent model to learn a trigonomy function (r=1-sin theta)
https://github.com/dnishimoto/python-deep-learning/blob/master/r%3D1-sin%20theta.ipynb
- I built a deep learning linear classifier to identify cultivator (deep learning intro with keras - linear classification.ipynb)
- I built a deep learning classifier to predict the flower types based on features
https://github.com/dnishimoto/python-deep-learning/blob/master/deep%20learning%20iris.ipynb
- I built a deep learning regressor to track the perimeters of a circle (deep learning circle chasing.ipynb)
- I applied gradient boost to predict death trends for three states (time series covid 19.ipynb)
https://github.com/dnishimoto/python-deep-learning/blob/master/time%20series%20covid%2019.ipynb
- I applied linear regression and gradient boost to predict the morality rate trends (time series with machine learning.ipynb)
- I applied deep learning to predict mpg based in hp, weight, displacement, and gears (linear regressor mpg and horse power.ipynb)
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