abdumajidhu Goto Github PK
Name: Semakula Abdumajidhu
Type: User
Bio: Developer / ML Researcher with great interest in Intelligent Applications.
Twitter: MajidSemakulaJr
Location: Toronto, Canada
Name: Semakula Abdumajidhu
Type: User
Bio: Developer / ML Researcher with great interest in Intelligent Applications.
Twitter: MajidSemakulaJr
Location: Toronto, Canada
Job search portal for job seekers and recruiters to connect on one common platform.
Managing channel letters
Regression and Classification task with sklearn.
Solving problems on probability, machine learning and programming. You will perform computations on the data with in the dataset. We shall perform basic preparation techniques as concerned with storage of data and models. And finally we shall cover some graph problems.
I will be analysing images in this tutorial. I will implement color maps, cropping, nagating, thresholding and factoring colors.
Image Enhancement describes methods to enhance images for either human consumption or for further automatic operations. Perhaps we need to reduce noise in the image; or, certain image details need to be emphasized or suppressed. Other appropriate terms often used are filter- ing, enhancement, or conditioning. The major notion is that the image contains some signal or structure, which we want to extract, along with uninteresting or unwanted variation, which we want to suppress. If de- cisions are made about the image, they are made at the level of a single pixel or its local neighborhood. We have already seen how we might la- bel an image pixel as object versus background or boundary versus not boundary. Image processing has both theory and methods that can found in sev- eral books. Only a few classical image processing concepts are covered in our class lectures. Most methods presented use the important notion that each pixel of the output image is computed from a local neighbor- hood of the corresponding pixel in the input image. However, a few of the enhancement methods are global in that all of the input image pixels are used in some way in creating the output image.
Samples for ML.NET, an open source and cross-platform machine learning framework for .NET.
Comparing chlorophyll content and spectral data to measure sooty mold effect in Cassava leaves.
Analyzing data, extracting and structuring using regex in python.
Use a haar classifier cascade to identify matches in a given image.
This notebook guides through some basic theory of working with features. From raw data to meaningful features.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.