Repositório criado para abrigar os notebooks com a listas de exercícios propostos pelo professor Gustavo Guanabara do canal Curso em Vídeo do YouTube durante o Curso de Python 3

Overview

Curso em Vídeo - Exercícios de Python 3

Sobre o repositório

Este repositório contém os notebooks com a listas de exercícios propostos pelo professor Gustavo Guanabara do canal Curso em Vídeo do YouTube durante o Curso de Python 3.

Até o presente momento, o curso possui 3 módulos chamados de Mundos. As listas de vídeos de cada um dos Mundos com as aulas teóricas e os respectivos exercícios encontra-se abaixo:

  1. Mundo 1: Fundamentos
  2. Mundo 2: Estruturas de Controle
  3. Mundo 3: Estruturas Compostas

A lista dos vídeos contendo "apenas" (são mais de 100!) os exercícios e as suas resoluções é: Exercícios de Python 3

Usando o Google Colab para fazer os exercícios

A ideia desse repositório é criar um notebook com a lista de exercícios de cada um dos Mundos do curso. Desta forma é possível importar esses notebooks para o ambiente do Google Colab e assim conseguir executar os códigos em Python sem a necessidade de uma instalação/configuração local do Python no computador.

Para isso, siga o seguinte passo a passo:

Passo 1

Copie o endereço deste repositório abaixo. Ele é o mesmo que está na barra de endereços do seu navegador conforme a Tela 1.

https://github.com/jplpereira/curso-em-video-exercicios-python

Tela 1

Passo 2

Abra o Google Colab clicando aqui. Ele vai apresentar as opções conforme a Tela 2 abaixo:

Tela 2

Passo 3

Selecione a opção GitHub, cole o link na caixa de texto e clique no botão da lupa. A lista de notebooks será atualizada. Ao lado de cada um deles, aparecerá o botão "Abrir notebook em uma nova guia" conforme a Tela 3 abaixo. Ele fará com que uma cópia do notebook selecionado seja adicionada no seu Google Drive.

Tela 3

Passo 4

O notebook vai abrir em uma nova guia do seu navegador pronto para você usar conforme a Tela 4.

Tela 4

Passo 5

Caso esteja logado com a sua conta do GitHub, clique no botão Star para ajudar esse repositório a ter mais visibilidade dentro da plataforma e chegar a mais pessoas interessadas em aprender Python.

Tela 5

Divirta-se assistindo as aulas do professor Guanabara e resolvendo os exercícios propostos. Espero que esse trabalho te ajude na sua jornada de aprendizado do Python!

Owner
João Pedro Pereira
João Pedro Pereira
Continual Learning of Long Topic Sequences in Neural Information Retrieval

ContinualPassageRanking Repository for the paper "Continual Learning of Long Topic Sequences in Neural Information Retrieval". In this repository you

0 Apr 12, 2022
Exploring Classification Equilibrium in Long-Tailed Object Detection, ICCV2021

Exploring Classification Equilibrium in Long-Tailed Object Detection (LOCE, ICCV 2021) Paper Introduction The conventional detectors tend to make imba

52 Nov 21, 2022
Implementing a simplified copy of Shazam application from scratch using MinHashing and LSH.

Building Shazam from scratch In this repository we tried to implement a simplified copy of the Shazam application able to tell you the name of a song

Arturo Ghinassi 0 Nov 17, 2022
Composing methods for ML training efficiency

MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training.

MosaicML 2.8k Jan 08, 2023
HiFi++: a Unified Framework for Neural Vocoding, Bandwidth Extension and Speech Enhancement

HiFi++ : a Unified Framework for Neural Vocoding, Bandwidth Extension and Speech Enhancement This is the unofficial implementation of Vocoder part of

Rishikesh (ऋषिकेश) 118 Dec 29, 2022
A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

24 Dec 13, 2022
Self-supervised Product Quantization for Deep Unsupervised Image Retrieval - ICCV2021

Self-supervised Product Quantization for Deep Unsupervised Image Retrieval Pytorch implementation of SPQ Accepted to ICCV 2021 - paper Young Kyun Jang

Young Kyun Jang 71 Dec 27, 2022
Implementation of FSGNN

FSGNN Implementation of FSGNN. For more details, please refer to our paper Experiments were conducted with following setup: Pytorch: 1.6.0 Python: 3.8

19 Dec 05, 2022
Replication Package for AequeVox:Automated Fariness Testing for Speech Recognition Systems

AequeVox Replication Package for AequeVox:Automated Fariness Testing for Speech Recognition Systems README under development. Python Packages Required

Sai Sathiesh 2 Aug 28, 2022
The undersampled DWI image using Slice-Interleaved Diffusion Encoding (SIDE) method can be reconstructed by the UNet network.

UNet-SIDE The undersampled DWI image using Slice-Interleaved Diffusion Encoding (SIDE) method can be reconstructed by the UNet network. For Super Reso

TIANTIAN XU 1 Jan 13, 2022
Pytorch implementation for DFN: Distributed Feedback Network for Single-Image Deraining.

DFN:Distributed Feedback Network for Single-Image Deraining Abstract Recently, deep convolutional neural networks have achieved great success for sing

6 Nov 05, 2022
This project implements "virtual speed" from heart rate monito

ANT+ Virtual Stride Based Speed and Distance Monitor Overview This project imple

2 May 20, 2022
Experimenting with computer vision techniques to generate annotated image datasets from gameplay recordings automatically.

Experimenting with computer vision techniques to generate annotated image datasets from gameplay recordings automatically. The collected data will then be used to train a deep neural network that can

Martin Valchev 3 Apr 24, 2022
Code from PropMix, accepted at BMVC'21

PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels This repository is the official implementation of Hard Sample Fil

6 Dec 21, 2022
Official Pytorch implementation of "Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video", CVPR 2021

TCMR: Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video Qualtitative result Paper teaser video Introduction This r

Hongsuk Choi 215 Jan 06, 2023
Kalidokit is a blendshape and kinematics solver for Mediapipe/Tensorflow.js face, eyes, pose, and hand tracking models

Blendshape and kinematics solver for Mediapipe/Tensorflow.js face, eyes, pose, and hand tracking models.

Rich 4.5k Jan 07, 2023
This repository collects project-relevant Isabelle/HOL formalizations.

Isabelle/HOL formalizations related to the AuReLeE project Formalization of Abstract Argumentation Frameworks See AbstractArgumentation folder for the

AuReLeE project 1 Sep 10, 2022
Alternatives to Deep Neural Networks for Function Approximations in Finance

Alternatives to Deep Neural Networks for Function Approximations in Finance Code companion repo Overview This is a repository of Python code to go wit

15 Dec 17, 2022
Unofficial TensorFlow implementation of the Keyword Spotting Transformer model

Keyword Spotting Transformer This is the unofficial TensorFlow implementation of the Keyword Spotting Transformer model. This model is used to train o

Intelligent Machines Limited 8 May 11, 2022
PantheonRL is a package for training and testing multi-agent reinforcement learning environments.

PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.

Stanford Intelligent and Interactive Autonomous Systems Group 57 Dec 28, 2022