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Projects in Awesome Lists by rakibhhridoy

A curated list of projects in awesome lists by rakibhhridoy .

https://github.com/rakibhhridoy/anomalydetectionintimeseriesdata-keras

Statistics, signal processing, finance, econometrics, manufacturing, networking[disambiguation needed] and data mining, anomaly detection (also outlier detection) is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. Typically the anomalous items will translate to some kind of problem such as bank fraud, a structural defect, medical problems or errors in a text. Anomalies are also referred to as outliers, novelties, noise, deviations and exceptions.

anomaly-detection autoencoder autoencoders deep-learning dropout keras lstm machine-learning numpy pandas python regularization tensorflow threshold

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/modelservingapplication-tensorflow-flask

Tensorflow deep learning model serving using flask. The template is simple as main concern is building the web app. Template making quite easy than serving,it shows all the steps needed to linking the model with our web application.

catvsdog-classifier classification-algorithims deep-learning flask flask-application python tensorflow webapp

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/sentimentanalysisindashboard-webapp

Sentiment analysis as dashboard in web server. Quick understandable and customized layout for any business application. This is based on positive, neutral and negative tweets in US location.

classification dashboard dashboard-application geovisualization machine-learning python sentiment-analysis streamlit-dashboard webapp

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/ctscanpredictioncovid19-tensorflow

Classifying covid positive and negative cases in ct-scan images. Though the data is not large enough, it can be processed and make prediction from the model. Images are quite similar thus the task became much complicated.

computer-vision covid-19 ctscan deep-learning deep-neural-networks image-classification image-processing keras machine-learning medical-image-analysis neural-network prognosis python

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/webappclassifierstreamlit-python

Machine Learning Training and Testing in Web App. It provide good learning interface for experimenting with different hyper parameter tuning and compare different algorithms with each other without writing code repeatedly.

classification hyperparameter-optimization hyperparameter-tuning logistic-regression machine-learning python random-forest streamlit support-vector-machines svm-classifier webapp

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/classifyoutersignals-spacesignals

Space signals comes with huge noise in it. For analyzing the signals we have to make sure there is as less noise as possible. Detecting the noise and denoising the signals is quite hard to do. As a Data Science Analytics one should have the capability to handling any kind of dataset.

autoencoders deep-learning denoising keras lstm machine-learning python signal-processing space space-signals

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/dsbot

A experimental bot for automation.

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/imageprocessing

Large amount of image processing is quite messy and time consuming,thus the working steps should be fast as well as accurate also. I've made sequential functions that is needed for processing data in TensorFlow and python. These functions made my work fast as it needed in commercial purposes.

augmentation deep-learning functional-programming image-manipulation image-processing keras machine-learning numpy python sequential-patterns tensorflow

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/imagedenoisingusing-autoencoders

Filtering out the noise presented in the image by auto-enconder algorithm in TensorFow and Keras. Rare images, unclean crime images,medical noise images can be denoised and find out the desired outcome by using auto-encoders.

autoencoder autoencoder-architecture autoencoder-neural-network deep-learning image-clean image-denoising keras python tensorflow theory

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/ecommerce-bi

Business Intelligent in e-commerce, there are many part of it. This is project that based on e-commerce business analysis, model building, predictions and forecasting.

business business-analytics business-intelligence customer-products customer-segmentation dashboard dashboards data-science e-commerce-project forecasting product-engineering python storytelling tableau time-series-analysis

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/supportvectormachinein-medical

Support vector machine in medical disease detection. Both linear and non-linear data can be fitted in svm through its kernel specialization In medical we focus on precision or recall rather than accuracy.

diabetes-prediction machine-learning medical precision-medicine recall-precision scikit-learn support-vector-machines svm

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/googleitcourse

This is a hands on specialization of Coursera Google IT Support Professional Certifications

bash certifcation cybersecurity google interactionwithos itsupport os powershell poweruser professional python

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/machinelearningwebappdeploy-flask

Developing a web app of machine learning model using flask is quite easy. One should have some basic knowledge in web development,not so much but quite a bit. It is just a introductory web app in flask classifying cat vs dog by deep learning model.

catvsdog catvsdog-classifier classification deep-learning flask flask-application html-css machine-learning model-deployment python web-application

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/bigdataanalysiswithapachespark-stockprice

Often we have to deal with large dataset, handling them with traditional method is quite tedious and time consuming. There's come the distributed method like apache spark. This repo consist distributed analysis of stock price which is quite large dataset.

apache-spark big-data pandas pyspark python spark-sql sprk-api stock stock-price-forecasting

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/machinelearning-featureselection

Before training a model or feed a model, first priority is on data,not in model. The more data is preprocessed and engineered the more model will learn. Feature selectio one of the methods processing data before feeding the model. Various feature selection techniques is shown here.

extratreesclassifier feature-selection gridsearchcv lasso-regression logistic-regression machine-learning numpy pandas pca rfe rfecv scikit-learn selectkbest

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/easywaydiveinto-datascience

Data Science is not as easy as it seems at first. The most problem faced by new learner are lack of resource knowledge as well as confusion in using the various resources. I hope this repository will benefit confusion learner.

algorithms algorithms-implemented bayesian-statistics data-science deep-learning deep-neural-networks linear-algebra machine-learning matplotlib multivariate-calculus numpy optimization pandas python scikit-learn scipy seaborn statistics statsmodels tensorflow

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/covid19analysisindashboard-tableau

Covid19 dashboard analysis of world,north america,south east Asia and their characteristics upon pandemic. Some interesting statistics is shown by the data. The increase rate make effect on death and recover rate quite periodic. Simulating those changes make more interactive.

covid-19 dashboard data-processing dataviz numpy pandas python statistics tableau tableau-dashboards

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/breastcanceranalysis-classificationclustering

Breast cancer prediction both in classification and clustering method for better understanding the data. Though clustering is different from classification,to finding the key aspect the data have,sometimes we need every possible way to catch behavior of the data.

breast-cancer-prediction breastcancer-classification classification classification-algorithm clustering eda hyperparameter-optimization machine-learning python scikit-learn supervised-learning unsupervised-learning

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/bioinformatics-geneticdatascience

This project is based on starting Bioinformatics as a life science student. Initializing a career as a Genetic Data Scientist and Bioinformatician.

bioinformatics biology biopython computer-science data-science genetic-data-science genetics genome-assembly genome-sequencing statistics

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/google-certification

All my project and course from Google. It contains IT Professional Certification, GCP PC, Networking In Cloud PC, Machine learning on GCP, Big Data hosted by Google on Coursera.

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/customersegmentation-clustering

Customer segmentation heavily use in business purpose. It is needed skill for business intelligence and applied machine learning engineer. This represent quite basic way the customer segmentation is done. In python the task is quite easy to do.

agglomerative-clustering clustering-algorithm customer ecommerce kmeans-clustering machine-learning scikit-learn scikitlearn-machine-learning segmentation unsupervised-learning unsupervised-machine-learning

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/regulartaskautomation

Regular file creation, moving staffs and others in python, golang and bash.

bash-script golang python

Last synced: 14 Oct 2024

https://github.com/rakibhhridoy/systemsreinstall

System configurations of desktops, servers and other machines. Automate with bash

arch-linux archlinux automation bash fedora system-administration

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/appliedmachinelearninghousing-regression

Let's take the Housing dataset which contains information about different houses in Boston. This data was originally a part of UCI Machine Learning Repository and has been removed now. We can also access this data from the scikit-learn library. The objective is to predict the value of prices of the house using the given features.

deep-learning housing-market housing-prices machine-learning numpy pandas python real-estate regression scikit-learn

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/predictingsequence-timeseriesanalysis

Time series data easy handling purposes in TensorFlow and python functional programming. Time Series data is handled and pre-processed by different steps,like making window of the data,splitting data for model purpose is also different than other processing methods. All has combined for easy access.

forecasting functional-programming keras lstm lstm-neural-networks moving-average numpy python tensorflow time-series windowed

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/adockerimage-website

Dockerrzing a app,website is quite handy as in different hardware the software act differently. Containerizing a website can be a example of this. Making a docker-image is a must having skills in model deplouing stage in Data Science.

docker docker-container html model-deployment website

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/comptia-linux-xk0-005

Certification preparation of comptia linux+ on udemy

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/gorust

learning golang and rust in the same time to understand core concept and best use cases of respective language Topics Resources

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/visualmachinelearning-yellowbrick

Yellowbrick wraps the scikit-learn and matplotlib to create publication-ready figures and interactive data explorations. It is a diagnostic visualization platform for machine learning that allows us to steer the model selection process by helping to evaluate the performance, stability, and predictive value of our models and further assist in diagnosing the problems in our workflow.

classification hyperparameter-tuning machine-learning model-evaluation model-view-presenter model-visualization python random-forest random-forest-classifier scikit-learn visualization xgboost xgboost-algorithm yellowbrick

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/handlingimbalanceddataset-business

It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase but by others illegally. Some huge transactions can also done by suspicious figure, it need to catch em.

auc business-intelligence fraud-detection imbalanced-data imbalanced-learning machine-learning oversampling precision recall smote transcations

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/exploratorydataanalysis-python

Exploratory data analysis is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task.

ab-testing chitest data-science eda exploratory-data-analysis ftest hypotheses hypothesis-testing inferential-statistics numpy pandas python statistical-analysis statistics statsmodels ttest

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/differentprojects

Some of my learning projects that I practice to launch in data science. Not all, but some of few that was stored in my local repository. It can be useful for beginner data science enthusiast. Explore and learn!

data-science deep-learning machine-learning mathematics matplotlib numpy pandas python scikit-learn seaborn statistics

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/neuralstyletransfer-tensorflow

One of the curious outcome of data science revolution is neural style transfer where nst algorithm merge two images, content and style, creating a artistic image of content image. Here TensorFlow is used to process images and lastly used nst algorithm.

deep-learning deep-neural-networks machine-learning neural-style-transfer neuralstyletransfer nst python tensorflow

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/natural-language-processing-steps

Preprocess data in nlp text classification and text sequence in TensorFlow. There's different steps in both classification and sequence task, thus it need different steps. These steps in TensorFlow is so much easy if you get into it.

classification embedded embedding-models feed keras natural-language-processing nlp python sentence sequence tensorflow text-analysis text-classification text-processing

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/buildingcandlestickcharts-tableau

Tableau provide wide range of Data visualization techniques in various aspect. Effect of Covid19 can be seen in stock price ups-down of big5. Data consist last 18 months daily stock.

amazon apple big5 candlestick-chart facebook microsoft stock-analysis stock-market tableau tableau-dashboards tesla trends yfinance yfinance-api

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/bankcustomerdataviz-powerbi

Bank customer analysis for detecting key loan targeted customers in different categories. The segment is divide by gender, education level, marital status and their characteristics in different state. All these analysis done in PowerBi report or dashboard.

bank banking customer customer-segmentation dataviz dataviz-tools powerbi powerbi-report

Last synced: 06 Nov 2024

https://github.com/rakibhhridoy/uscrimeanalysis-appliedstatistics

Detecting the key reason for crime(manslaughter) happened in 30 years. There's a lot of aspect present in the data published by US government. The data and the finding can be used in any country prospect,if not all but handy few.

ab-testing applied-statistics crime crime-analysis crime-prediction crime-statistics eda exploratory-data-analysis exploratory-data-visualizations hypothesis-testing machine-learning python statistical-analysis statistical-learning statsmodels visualization

Last synced: 06 Nov 2024