Ciência de Dados Complexos

Curso sobre modelos de linguagem oferecido pela Google. É possível colocar legendas em Português. https://www.cloudskillsboost.google/course_templates/539

Para quem tiver interesse em fazer um MBA em Ciência de Dados, o curso no ICMC-USP é uma ótima opção. Reportagem do Estadão: https://publicacoes.estadao.com.br/guiadomba/formacao-com-a-mao-na-massa/

Livro de Deep Learning disponível onine: https://udlbook.github.io/udlbook/

Curso de NLP na Universidade de Stanford: https://www.youtube.com/playlist?list=PLoROMvodv4rMFqRtEuo6SGjY4XbRIVRd4

Excelente tutorial sobre predição de séries temporais: https://colab.research.google.com/drive/1X1DJF4pZlklIt5srQnyTYoyFVLunr_OQ

Curso online sobre Aprendizado de Máquina na Cornell University. Se quiser ver em Português, clique com o botão direito do mouse e selecione Translate (traduzir). Conteúdo excelente. https://kuleshov-group.github.io/aml-book/intro.html

+800 cursos de Ciência da Computação online e de graça. https://github.com/Developer-Y/cs-video-courses

Curso online de Aprendizado de Máquina. É possível ativar a legenda em Pt. https://www.youtube.com/playlist?list=PLG19vXLQHvSC2ZKFIkgVpI9fCjkN38kwf

Curso online de Aprendizado de Máquina. É possível ativar a legenda em Pt. https://www.youtube.com/playlist?list=PLG19vXLQHvSC2ZKFIkgVpI9fCjkN38kwf

Workshop: “Inteligência artificial, Graduação e Química” https://www.youtube.com/watch?v=ufydN4XP0qA

- Geph - https://gephi.org - Gephisto- https://lnkd.in/diSp3BWN - VOSviewer - https://www.vosviewer.com - Cytoscape - https://cytoscape.org - Kumu - https://kumu.io - GraphInsight - https://lnkd.in/d5XnkWJr - NodeXL - https://nodexl.com - Orange - https://lnkd.in/dZU8Zx3D - Graphia - https://graphia.app - Graphistry - https://www.graphistry.com - SocNetV - https://socnetv.org - Tulip - https://lnkd.in/dtc_BD33 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐥𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧: - networkx - https://lnkd.in/dKCCXjif - graphviz - https://lnkd.in/dtrTeqRv - pydot - https://lnkd.in/dA46YZvy - python-igraph - https://lnkd.in/dCGsRXh2 - pyvis - https://lnkd.in/dVrQ64nN - ipycytoscape - https://lnkd.in/d-hJjDdG - pygsp - https://lnkd.in/dS7s-A_v - graph-tool - https://lnkd.in/dvytUzdu - nxviz - https://lnkd.in/duHbKGPN - py2cytoscape - https://lnkd.in/dWUU8TZH - ipydagred3 - https://lnkd.in/diXgFWMD - ipysigma - https://lnkd.in/dP55J5et - Py3Plex - https://lnkd.in/dhwe7f_g - net wulf - https://lnkd.in/dxrHAm2P

- Geph - https://gephi.org - Gephisto- https://lnkd.in/diSp3BWN - VOSviewer - https://www.vosviewer.com - Cytoscape - https://cytoscape.org - Kumu - https://kumu.io - GraphInsight - https://lnkd.in/d5XnkWJr - NodeXL - https://nodexl.com - Orange - https://lnkd.in/dZU8Zx3D - Graphia - https://graphia.app - Graphistry - https://www.graphistry.com - SocNetV - https://socnetv.org - Tulip - https://lnkd.in/dtc_BD33 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐥𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧: - networkx - https://lnkd.in/dKCCXjif - graphviz - https://lnkd.in/dtrTeqRv - pydot - https://lnkd.in/dA46YZvy - python-igraph - https://lnkd.in/dCGsRXh2 - pyvis - https://lnkd.in/dVrQ64nN - ipycytoscape - https://lnkd.in/d-hJjDdG - pygsp - https://lnkd.in/dS7s-A_v - graph-tool - https://lnkd.in/dvytUzdu - nxviz - https://lnkd.in/duHbKGPN - py2cytoscape - https://lnkd.in/dWUU8TZH - ipydagred3 - https://lnkd.in/diXgFWMD - ipysigma - https://lnkd.in/dP55J5et - Py3Plex - https://lnkd.in/dhwe7f_g - net wulf - https://lnkd.in/dxrHAm2P- Geph - https://gephi.org - Gephisto- https://lnkd.in/diSp3BWN - VOSviewer - https://www.vosviewer.com - Cytoscape - https://cytoscape.org - Kumu - https://kumu.io - GraphInsight - https://lnkd.in/d5XnkWJr - NodeXL - https://nodexl.com - Orange - https://lnkd.in/dZU8Zx3D - Graphia - https://graphia.app - Graphistry - https://www.graphistry.com - SocNetV - https://socnetv.org - Tulip - https://lnkd.in/dtc_BD33 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐥𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧: - networkx - https://lnkd.in/dKCCXjif - graphviz - https://lnkd.in/dtrTeqRv - pydot - https://lnkd.in/dA46YZvy - python-igraph - https://lnkd.in/dCGsRXh2 - pyvis - https://lnkd.in/dVrQ64nN - ipycytoscape - https://lnkd.in/d-hJjDdG - pygsp - https://lnkd.in/dS7s-A_v - graph-tool - https://lnkd.in/dvytUzdu - nxviz - https://lnkd.in/duHbKGPN - py2cytoscape - https://lnkd.in/dWUU8TZH - ipydagred3 - https://lnkd.in/diXgFWMD - ipysigma - https://lnkd.in/dP55J5et - Py3Plex - https://lnkd.in/dhwe7f_g - net wulf - https://lnkd.in/dxrHAm2P- Geph - https://gephi.org - Gephisto- https://lnkd.in/diSp3BWN - VOSviewer - https://www.vosviewer.com - Cytoscape - https://cytoscape.org - Kumu - https://kumu.io - GraphInsight - https://lnkd.in/d5XnkWJr - NodeXL - https://nodexl.com - Orange - https://lnkd.in/dZU8Zx3D - Graphia - https://graphia.app - Graphistry - https://www.graphistry.com - SocNetV - https://socnetv.org - Tulip - https://lnkd.in/dtc_BD33 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐥𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧: - networkx - https://lnkd.in/dKCCXjif - graphviz - https://lnkd.in/dtrTeqRv - pydot - https://lnkd.in/dA46YZvy - python-igraph - https://lnkd.in/dCGsRXh2 - pyvis - https://lnkd.in/dVrQ64nN - ipycytoscape - https://lnkd.in/d-hJjDdG - pygsp - https://lnkd.in/dS7s-A_v - graph-tool - https://lnkd.in/dvytUzdu - nxviz - https://lnkd.in/duHbKGPN - py2cytoscape - https://lnkd.in/dWUU8TZH - ipydagred3 - https://lnkd.in/diXgFWMD - ipysigma - https://lnkd.in/dP55J5et - Py3Plex - https://lnkd.in/dhwe7f_g - net wulf - https://lnkd.in/dxrHAm2P

O boxplot é um tipo de gráfico bastante importante, mas há várias alternativas interessantes. Esse link mostra várias delas: https://z3tt.github.io/beyond-bar-and-box-plots/