Fast and customizable framework for automatic ML model creation (AutoML)
A multi-platform GUI for bit-based analysis, processing, and visualization
Binary and Categorical Focal loss implementation in Keras.
autosklearn-zeroconf is a fully automated binary classifier. It is based on the AutoML challenge winner auto-sklearn. Give it a dataset with known outcomes (labels) and it returns a list of predicted outcomes for your new data. It even estimates the precision for you! The engine is tuning massively parallel ensemble of machine learning pipelines…
2017-CCF-BDCI-企业经营退出风险预测：9th/569 (Top 1.58%)
[AACL 2020] Toxic Language Detection in Social Media for Brazilian Portuguese: New Dataset and Multilingual Analysis
2018-腾讯广告算法大赛-相似人群拓展(初赛)：10th/1563 (Top 0.64%)
Fully supervised binary classification of skin lesions from dermatoscopic images using an ensemble of diverse CNN architectures (EfficientNet-B6, Inception-V3, SEResNeXt-101, SENet-154, DenseNet-169) with multi-scale input.
Custom Loss Functions and Evaluation Metrics for XGBoost and LightGBM
Malicious URL detector using keras recurrent networks and scikit-learn classifiers
Practical ML and NLP with examples.
Repository for My HuggingFace Natural Language Processing Projects
WNUT-2020 Task 2: Identification of informative COVID-19 English Tweets
LightGBM for handling label-imbalanced data with focal and weighted loss functions in binary and multiclass classification
Machine learning enabled dropper
Binary Image Classification in TensorFlow
Glaucoma detection automation project. Trained a binary image classifier using CNNs and deployed as a streamlit web app. It takes eye (retinal scan) image as input and outputs whether the person is affected by glaucoma or not.
Online machine learning algorithms (based on OLL C++ library)
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