Pinned Repositories
CKMeansTreeClustering_consensus
CKMedoidsTreeClustering
A new fast method for building multiple consensus trees using k-medoids
CNNTrees
dash-object-detection
Dash Demo App - Object Detection Application, using MobileNet v1
dash-phylogeny
Interactive phylogeny trees with Dash
dataset
functions-demo
KMeansSuperTreeClustering
k-means, classification, phylogenetic tree, bioinformatic, supertrees
TahiriNadia.github.io
Tahiri Lab website
TahiriNadia's Repositories
TahiriNadia/dataset
TahiriNadia/KMeansSuperTreeClustering
k-means, classification, phylogenetic tree, bioinformatic, supertrees
TahiriNadia/2018-web
TahiriNadia/course-v3
The 3rd edition of course.fast.ai
TahiriNadia/creative-theme-jekyll
TahiriNadia/dl-workshop
A deep learning workshop, done from scratch, taught without any frameworks.
TahiriNadia/docs
TensorFlow documentation
TahiriNadia/DoubleRecViz
DoubleRecViz is a tool for visualizing and editing double reconciliations between phylogenetic trees at three levels: transcript, gene and species.
TahiriNadia/ElleCode-ACM
TahiriNadia/forestry.io
Forestry.io website
TahiriNadia/hawc
Health assessment workspace collaborative
TahiriNadia/heroku-builds
Builds API CLI plugin
TahiriNadia/hoverboard
Conference website template
TahiriNadia/IFT6390
TahiriNadia/jekyll-minimal-mistakes-forestry
TahiriNadia/joss
The Journal of Open Source Software
TahiriNadia/Machine-Learning-with-Python
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
TahiriNadia/ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
TahiriNadia/ml-sutdy-jam2019-montreal
code and slides from ml sutdy jam 2019 in Montreal
TahiriNadia/plotly.py
An open-source, interactive graphing library for Python :sparkles:
TahiriNadia/QSAR-1
TahiriNadia/QSAR_PTR
QSAR placental transfer ratios
TahiriNadia/rspci
Analysis of fragments contributions calculated by SPCI software
TahiriNadia/samplchallenges.github.io
Information on the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) series of blind prediction challenges for computational chemistry
TahiriNadia/scikit-learn
scikit-learn: machine learning in Python
TahiriNadia/stanford-cs-229-machine-learning
VIP cheatsheets for Stanford's CS 229 Machine Learning
TahiriNadia/test
TahiriNadia/testNadia
TahiriNadia/vscode-r
R Tools for VS Code
TahiriNadia/WTM-APP
An App Template For GDG DevFest