rakibhhridoy Goto Github PK

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.

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.

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.

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.

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.

bioinformatics-geneticdatascience

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

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.

build-your-own-x

Master programming by recreating your favorite technologies from scratch.

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.

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.

comptia-linux-xk0-005

Certification preparation of comptia linux+ on udemy

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.

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.

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.

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!

dsbot

A experimental bot for automation.

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.

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.

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.

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.

googleitcourse

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

gorust

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

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.

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.

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.

linuxadministration

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.

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.

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.

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.