Search Results for "jd-core" - Page 8

Retrieval-Based Conversational Model in Tensorflow is a project implementing a retrieval-based conversational model using a dual LSTM encoder architecture in TensorFlow, illustrating how neural networks can be trained to select appropriate responses from a fixed set of candidate replies rather than generate them from scratch. The core idea is to embed both the conversation context and potential replies into vector representations, then score how well each candidate fits the current dialogue, choosing the best match accordingly. Designed to work with datasets like the Ubuntu Dialogue Corpus, this codebase includes data preparation, model training, and evaluation components for building and assessing dialog models that can handle multi-turn conversations.

This repository contains lecture notes, slides, assignments, and code for a university-level Natural Language Processing course. It spans core NLP topics such as language modeling, sequence tagging, parsing, semantics, and discourse, alongside modern machine learning methods used to solve them. Students work through programming exercises and problem sets that build intuition for both classical algorithms (like HMMs and CRFs) and neural approaches (like word embeddings and sequence models). ...

Locally Weighted Projection Regression (LWPR) is a fully incremental, online algorithm for non-linear function approximation in high dimensional spaces, capable of handling redundant and irrelevant input dimensions. At its core, it uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space. A locally weighted variant of Partial Least Squares (PLS) is employed for doing the dimensionality reduction. Please cite: [1] Sethu Vijayakumar, Aaron D'Souza and Stefan Schaal, Incremental Online Learning in High Dimensions, Neural Computation, vol. 17, no. 12, pp. 2602-2634 (2005)...

This project is a complete cross-platform (Windows, Linux) framework for Evolutionary Computation in pure python. See the project site at http://pyevolve.sourceforge.net or the blog at http://pyevolve.sourceforge.net/wordpress

Python Machine learning library with multi-core support. Wraps existing ML libraries in order to be able to run and analyse experiments with one front-end API. Currently supports MLP, GA, GP, ESN and RBF algorithms.

OCR Reader is a lightweight Windows utility designed to extract text from PDF files and images using OCR (Tesseract engine). The tool supports template-based parsing, allowing structured output into CSV or TXT without manual coding. Core components Tesseract OCR engine Poppler (PDF rendering) Template-based extraction system Homepage: https://martan1484.github.io/OCR_Reader

...Scripthea offers a structured environment for building, testing, and refining prompts, making it an invaluable tool for artists, designers, and AI enthusiasts seeking greater control over their creative outputs. At its core, Scripthea simplifies prompt engineering by breaking down prompts into two components: cues (descriptive text) and modifiers (attributes like style, lighting, or artist references). This modular approach allows users to experiment with various combinations, facilitating a more systematic exploration of visual styles and themes. ...

Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection - https://github.com/Tessellate-Imaging/Monk_Object_Detection. Monk object detection is our take on assembling state of the art object detection, image segmentation, pose estimation algorithms at one place, making them low code and easily configurable on any machine...