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dify

An Open-Source Assistants API and GPTs alternative. Dify.AI is an LLM application development platform. It integrates the concepts of Backend as a Service and LLMOps, covering the core tech stack required for building generative AI-native applications, including a built-in RAG engine.

dmls-book

Summaries and resources for Designing Machine Learning Systems book (Chip Huyen, O'Reilly 2022)

git-from-scratch

go-project-layout

Standard Go Project Layout

golearn

Machine Learning for Go

machine-learning-systems-design

A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"

mimic-code

MIMIC Code Repository: Code shared by the research community for the MIMIC-III database

movie_recommender_system_project

Various recommender systems are used in various fields, such as playlists for video and music services, product recommendations for online stores, and content recommendations for social media platforms. In this project, we are creating a movie recommendation. The dataset was found from the movies/tv rating website called IMDB. The website includes data from nearly all the movies, tv, shorts and web videos in existence. The original dataset was acquired from datasets.imdbws.com which is a self hosted link from the creators of the website. The dataset consists of 7 TSV files totaling 7 GB of data. In modern society, due to the prevalence of the Internet, people have too many choices to choose from, which is why we need a recommender system. As an example, Netflix has a large selection of movies. People have a hard time selecting the items that they actually want to see, even though the amount of available information has increased. Recommender systems can help with this

predicting-the-success-of-bank-telemarketingusing-machine-learning

In this study, we examine telemarketing practices for promoting long-term bank deposits to poten-tial bank customers. A number of machine learning algorithms, like Decision Tree (DT) and Logistic Regression (LR), were employed to determine the subscription of long-term bank deposits. The results confirm that the DT model provides an f1-score of 0.90 compared to LR, which has an f1-score of 0.73 for the positive class, making DT the better model for predicting the potential customers who have an interest in long-term deposits through telemarketing. Notably, many financial services providers adopted telemarketing strategy to reach out tothe new customers and to provide better services to existing customers, and to meet their specific needs. In future marketing campaigns, the results of the machine learning model could be used by managers to prioritize and select which customers to contact next. Index Terms — Decision Tree, Logistic Regression, Resilient Distributed Dataset (RDD), Telemarketing

seam-carving_computer_vision

Most of digital images are viewed in different devices with a variety of resolutions. the shift of multiple device make the resolution of viewing images difficult because they usually are resized to shape limited space.Resizing an image’s height and width can cause distortion if not using an effective algorithm. One such algorithm is seam carving which allows for resizing by still maintaining the important features of an image.This allows you to make carvings of the image but keep the most important features of the image during the resizing process. The purpose of seam carving algorithm is image retargeting, which is the issue in images displaying without deformation on media of various sizes such as cell phones, or projection screens. In this paper we will introduce multiple applications of seam craving algorithm, and discuss in deep the method about it.In addition, we will also shows a new energy criterion for improving the visual quality of retargeted images and videos. The original seam carving operator focuses on deleting seams with the least amount of energy while ignoring the energy put into the photos and video by applying the operator. To combat this, the new criterion for reducing seams will be to look forward. This method is referred as forward energy it predicts which pixels would be nearest after removing a seam and uses that data to suggest the optimum seam to eliminate. This is in contrast to the traditional approach’s backward energy.

semantic-chunkers

userexperience_generalassembly

General Assembly’s User Experience Design Part-time course teaches students how to use the wants, behaviors, and needs of customers, to shape the functional design of everyday digital applications. Overview Congratulations on joining us at MiSK Academy for the UX Design Part-Time course! We are excited to have you join our community and are looking forward to working with you soon. In this course, students learn how to analyze business goals, use research methods to identify user needs, wireframe interfaces using design best practices and build prototypes to test through usability testing.

virtualrealitydevelopernanodegree_projects

In this nanodegree we study the latest tools and technologies in the exciting field of VR! Learn from industry experts like Google, Unity, and HTC, and immerse yourself in Virtual Reality. Focus on the fundamentals of using the Unity Game Engine to build beautiful and performant VR scenes, and learn how to make your VR experience more dynamic and responsive by using C# programming in the Unity interface.