Thalita's Projects
Repositório para o #alurachallengedatascience1
Repositorio para aula do dia 16
Config files for my GitHub profile.
Página de formulário com HTML e CSS
This Contain 9 Machine Learning Projects that I have done while understanding ML Concepts.
Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.
My IPython Notebooks
Jupyter notebook and datasets from the pandas Q&A video series
Projeto de datascience da escola Digital House
Projeto Integrador turma de Meio Ambiente DH
Machine Learning with Text in scikit-learn
Resources for the PyCon 2017 tutorial, "Exploratory data analysis in python"
Jupyter notebooks from the scikit-learn video series
Start here if... You're new to data science and machine learning, or looking for a simple intro to the Kaggle prediction competitions. Competition Description The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships. One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class. In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy. Practice Skills Binary classification Python and R basics
Launch a development local Server with live reload feature for static & dynamic pages.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent