benjikcf Goto Github PK

adaptive-risk-parity

Adaptive Risk Parity strategy for 3x leveraged ETF

advanced-computer-vision-with-tensorflow

algorithm

introduction to algorithm example

amex_transformer

apache-spark-book1

Apache Spark in 24 Hours, Sams Teach Yourself

autoencoder-keras

automl-example

automl example

awd-lstm-sentiment-classifier

Using a pretrained wikitext language model and its embedding to create a sentiment classifier for IMDB movie review.

awesome-language-dataset

Collection of all language dataset for finetuning LLM

bot-sort

BoT-SORT: Robust Associations Multi-Pedestrian Tracking

cateogorical2

kaggle categorical competition

chatgpt-retrieval-plugin

The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language.

chinese-llama-alpaca

中文LLaMA&Alpaca大语言模型+本地部署 (Chinese LLaMA & Alpaca LLMs)

chinesepythontutorial

myexercises

codewars

Challenge myself on kata, created by the community to strengthen different skills. Master current language of choice, or expand understanding of a new one.

custom-and-distributed-training-with-tensorflow

custom-models-layers-and-loss-functions-with-tensorflow

deep-neural-network-from-udacity

About this Course Machine learning is one of the fastest-growing and most exciting fields out there, and deep learning represents its true bleeding edge. In this course, you'll develop a clear understanding of the motivation for deep learning, and design intelligent systems that learn from complex and/or large-scale datasets. We'll show you how to train and optimize basic neural networks, convolutional neural networks, and long short term memory networks. Complete learning systems in TensorFlow will be introduced via projects and assignments. You will learn to solve new classes of problems that were once thought prohibitively challenging, and come to better appreciate the complex nature of human intelligence as you solve these same problems effortlessly using deep learning methods. We have developed this course with Vincent Vanhoucke, Principal Scientist at Google, and technical lead in the Google Brain team. **Note: This is an intermediate to advanced level course offered as part of the Machine Learning Engineer Nanodegree program. It assumes you have taken a first course in machine learning, and that you are at least familiar with supervised learning methods.

efficientnet

Implementation of efficientnet in fastai

fastai-part2-2019

Using pure python and pytorch to rebuild Fast.ai library

generative-deep-learning-with-tensorflow

genetic-algorithm-for-radiation

Gamma Radiation Classifier and use Genetic Programming to pick the best Machine Learning model + hyper-parameters FOR US in 40 lines of Python.

gpt-llama.cpp

A llama.cpp drop-in replacement for OpenAI's GPT endpoints, allowing GPT-powered apps to run off local llama.cpp models instead of OpenAI.

gstreamer-install

hands-on-machine-learning

Contains Jupyter Notebooks/Resources provided by the author and my work on problem sets.

hong-kong-big-data-downloader-

A data downloader of Hong Kong Economic indicator. This includes HK Housing price (Centa-City Leading Index), HK GDP, HK Inflation, HSI, HK Unemployment, Chinese housing price, Chinese GDP, Chinese Inflation, CSI300, SP500, US interest, USD:RMB

hugginface_testing

ibm-ai-engineering

image-multiclass-classification

linear-support-vector-classifier-for-hong-kong-stock-price

Using Linear Support Vector Classification to analyze individual stock from Hong Kong