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100-days-of-code

Fork this template for the 100 days journal - to keep yourself accountable (multiple languages available)

aceleradev-data-science-1

active_learning

This repository aims to demonstrate the active learning technique at the machine learning experience meetup

agenda_django

agenda com o framework django

ainotebooks

Jupyter Notebooks sobre Inteligência Artificial

bike-sharing-demand

In this project, I'm using the AutoGluon library to train several models for the Bike Sharing Demand competition in Kaggle.

bit-of-data-science-and-scikit-learn

Youtube tutorial associated content

bootstrap

Utilizando Bootstrap

chatbot

Demonstração de um chatbox utilizando o framework TensorFlow

complete-web-developer-manual

All resources and notes from the Complete Web Developer in 2018: Zero to Mastery course

courseraml

I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!

data-science--cheat-sheet

Cheat Sheets

data_science_projects

Projects developed through the course "Python for Data Science and Machine Learning Bootcamp"

datascience-pizza

🍕 Repositório para juntar informações sobre materiais de estudo em análise de dados e áreas afins, empresas que trabalham com dados e dicionário de conceitos

datascience_bootcamp

deeplearning.ai-summary

This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.

deploy_ml_model_heroku_fastapi

In this project, it will be develop a classification model on publicly available Census Bureau data. It will be create unit tests to monitor the model performance on various slices of the data. Then, deploy the model using the FastAPI package and create API tests. Both the slice-validation and the API tests will be incorporated into a CI/CD framework using GitHub Actions. Two datasets will be provided in the starter code on the following page to experience updating the dataset and model in git and DVC.

deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

dog_breed_classification_sagemaker

Use AWS Sagemaker to train a pretrained model that can perform image classification by using the Sagemaker profiling, debugger, hyperparameter tuning and other good ML engineering practices. This can be done on either the provided dog breed classication data set or one of your choice.

dynamic-risk-assessment-system

frod

First GitHub

frodmvp

mvp frod

genre_classification

Final exercise of the Udacity class on Machine Learning workflows

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hello_django

Projeto utilizando o framework django

html5_css3

how to use html5 and CSS3

inventory_monitoring_sagemaker

Inventory Monitoring at Distribution Centers using Deep Learning

ipyvolume

3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL

javascript

JavaScript

jquery_ajax

Utilização de jquery e ajax