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ai-nanodegree

My projects from Udacity's Artificial Intelligence Nanodegree

autokeras

accessible AutoML for deep learning.

blog

Personal Blog

challenges-machine-learning

Code of Competencies This repository contains codes and notebooks with exploration data of the different platform competitions, such as: Kaggle, Tianchi, etc. In addition, I put more codes with modification in my original codes.

classyvision

An end-to-end PyTorch framework for image and video classification

code_search

Code For Medium Article: "How To Create Natural Language Semantic Search for Arbitrary Objects With Deep Learning"

conventions

∞ Priceloop Engineering Conventions for Python, Golang, Git Workflow etc

crash_course_pandas

Notebook of the Crash Course of Pandas 2018

cross-lingual-short-text-matching-of-question-pairs

Mini project about Cross-lingual Short-text Matching.

cs228-material_en_esp

Tutorial de la Universidad de Stanford para los cursos cs228 y cs231 en Español

cs231n.github.io

Public facing notes page

dask_vs_pyspark

Exploring the differences and similarities between Dask and PySpark in common use cases.

deepfake_review

Repository with DeepFake codes and experiments

deepspeech

A TensorFlow implementation of Baidu's DeepSpeech architecture

descriptor_track

Test_Envorinment

dive_into_fastai

Fastai and fastcore exploration

dlegor.github.io

Personal Page

drqa

Reading Wikipedia to Answer Open-Domain Questions

examples

TensorFlow examples

examples-spark

facenet

Face recognition using Tensorflow

feature-engineering

Feature engineering: examples for different types of data and problems.

few-shot-text-classification

figaro

Figaro Programming Language and Core Libraries

gan

Tooling for GANs in TensorFlow

google-cloud-python

Google Cloud Client Library for Python

hail

Scalable genomic data analysis.

hub

A library for transfer learning by reusing parts of TensorFlow models.

learning-spark

Example code from Learning Spark book

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.