Eric's repositories
machine-learning-for-software-engineers
A complete daily plan for studying to become a machine learning engineer.
Machine-Learning-With-Python
此项目是我在学习《机器学习实战》这本书时的代码记录情况,用python实现,当然也会包括一些其他的机器学习算法,使用Python实现
AI_Project
AI_Project
Auto-GPT
An experimental open-source attempt to make GPT-4 fully autonomous.
classification_models
Classification models trained on ImageNet. Keras.
CVPR2021-Papers-with-Code
CVPR 2021 论文和开源项目合集
Data-Competition-TopSolution
Data competition Top Solution 数据竞赛top解决方案开源整理
deep-learning-models
Keras code and weights files for popular deep learning models.
Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
KnowledgeGraphCourse
东南大学《知识图谱》研究生课程
LightGBM
A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.
Medical-Image-Classification-using-deep-learning
Tumour is formed in human body by abnormal cell multiplication in the tissue. Early detection of tumors and classifying them to Benign and malignant tumours is important in order to prevent its further growth. MRI (Magnetic Resonance Imaging) is a medical imaging technique used by radiologists to study and analyse medical images. Doing critical analysis manually can create unnecessary delay and also the accuracy for the same will be very less due to human errors. The main objective of this project is to apply machine learning techniques to make systems capable enough to perform such critical analysis faster with higher accuracy and efficiency levels. This research work is been done on te existing architecture of convolution neural network which can identify the tumour from MRI image. The Convolution Neural Network was implemented using Keras and TensorFlow, accelerated by NVIDIA Tesla K40 GPU. Using REMBRANDT as the dataset for implementation, the Classification accuracy accuired for AlexNet and ZFNet are 63.56% and 84.42% respectively.
openai-cookbook
Examples and guides for using the OpenAI API
Real-Time-Person-Removal
Removing people from complex backgrounds in real time using TensorFlow.js in the web browser
scikit-learn
scikit-learn: machine learning in Python
skincancer
Skin cancer detection project
tensorflow-windows-wheel
Tensorflow prebuilt binary for Windows
TianChi_IJCAI17_KouBei
2017天池口碑商家客流量预测
USTC-CS-Courses-Resource
:heart:**科学技术大学计算机学院课程资源(https://mbinary.xyz/ustc-cs/)
VicEnergySave.github.io
VicEnergySave