{ "cells": [ { "cell_type": "markdown", "id": "e17872b7-6436-4310-a263-c624d9b1419a", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "
\n", " \n", "
\n", "\n", "# Aprendizaje Profundo" ] }, { "cell_type": "markdown", "id": "9410923b-9f52-40c6-9563-a390ef1708f6", "metadata": {}, "source": [ "#
Ciencia de Datos
" ] }, { "cell_type": "markdown", "id": "50508e80-b758-446e-b1d5-ab318d958f0c", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Profesores" ] }, { "cell_type": "markdown", "id": "b2e750f3-cc8c-4ce9-89d4-50c535a91639", "metadata": {}, "source": [ "1. Alvaro Montenegro, PhD, ammontenegrod@unal.edu.co\n", "1. Campo Elías Pardo, PhD, cepardot@unal.edu.co\n", "1. Daniel Montenegro, Msc, dextronomo@gmail.com \n", "1. Camilo Torres, Msc, cjtorresj@unal.edu.co" ] }, { "cell_type": "markdown", "id": "04c2b686-b3c0-4bbc-91e8-1d40a5b7bd8a", "metadata": {}, "source": [ "## Asesora Medios y Marketing digital" ] }, { "cell_type": "markdown", "id": "a27368ec-af97-4720-b27d-b92d18d8280a", "metadata": {}, "source": [ "5. Maria del Pilar Montenegro, pmontenegro88@gmail.com\n", "6. Jessica López Mejía, jelopezme@unal.edu.co" ] }, { "cell_type": "markdown", "id": "5705572f-d2c6-4883-abec-2d677cfc86c2", "metadata": {}, "source": [ "## Jefe Jurídica" ] }, { "cell_type": "markdown", "id": "fd1c806b-91e5-43df-b91f-1f976e8bc9a6", "metadata": {}, "source": [ "7. Paula Andrea Guzmán, guzmancruz.paula@gmail.com" ] }, { "cell_type": "markdown", "id": "3bbeb9d2-43ca-4a38-b974-c2a651432778", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "## Coordinador Jurídico" ] }, { "cell_type": "markdown", "id": "0d3ebad2-1d3f-4aee-b2d4-4925cfed9dc0", "metadata": {}, "source": [ "8. David Fuentes, fuentesd065@gmail.com" ] }, { "cell_type": "markdown", "id": "73907297-dde5-4563-abda-b496eb147dc7", "metadata": {}, "source": [ "## Desarrolladores Principales" ] }, { "cell_type": "markdown", "id": "561fad8b-4dc3-478f-a2e8-5deeb1cd824b", "metadata": {}, "source": [ "9. Dairo Moreno, damoralesj@unal.edu.co\n", "10. Joan Castro, jocastroc@unal.edu.co\n", "11. Bryan Riveros, briveros@unal.edu.co\n", "12. Rosmer Vargas, rovargasc@unal.edu.co" ] }, { "cell_type": "markdown", "id": "2a832cfe-5b62-430d-9a2d-c96e4a3128d6", "metadata": {}, "source": [ "## Expertos en Bases de Datos" ] }, { "cell_type": "markdown", "id": "4be34a15-84c3-4d81-8880-b4fc21357978", "metadata": {}, "source": [ "13. Giovvani Barrera, udgiovanni@gmail.com\n", "14. Camilo Chitivo, cchitivo@unal.edu.co" ] }, { "cell_type": "markdown", "id": "2a0da79b-44dc-460c-ac1e-b71ade087a9c", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "## Contenido" ] }, { "cell_type": "markdown", "id": "22434174-4335-4e04-91b4-adc7c3cd665a", "metadata": {}, "source": [ "* [Nuestro equipo docente](#Nuestro-equipo-docente)" ] }, { "cell_type": "markdown", "id": "3fb53d12-1afd-4c49-b625-58fff4af141f", "metadata": {}, "source": [ "[Que es la ciencia de datos](#Que-es-la-ciencia-de-datos)\n", "* [Identificar el problema y el objetivo](#Identificar-el-problema-y-el-objetivo)\n", "* [Capturar y recolectar de datos](#Capturar-y-recolectar-de-datos)\n", "* [Transformar](Transformar)\n", "* [Explorar, análizar, modelar, visualizar y concluir](#Concluir-y-visualizar)" ] }, { "cell_type": "markdown", "id": "578ed542-cfa4-46ec-9f1b-c97a83ed46e9", "metadata": {}, "source": [ "[Claves de desarrollo en ciencia de datos](#Claves-de-desarrollo-en-ciencia-de-datos)\n", "* [Digitalización de documentos](#Digitalización-de-documentos)\n", "* [Matemáticas](#Matemáticas)\n", "* [Transformación de problemas](#Transformación-de-problemas)\n", "* [Tecnología](#Tecnología)\n", "* [Arquitecturas Neuronales Paradigma](#Arquitecturas-Neuronales-Paradigma)" ] }, { "cell_type": "markdown", "id": "64659b3d-d30a-46cf-885f-f576cb4ee62e", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Nuestro equipo docente" ] }, { "cell_type": "markdown", "id": "d89daa42-ebd4-4ee5-915c-3a7a1a5c69b3", "metadata": {}, "source": [ "### Alvaro Montenegro, PhD" ] }, { "cell_type": "markdown", "id": "21ab42a1-2a8a-44fb-8c61-b8494581a523", "metadata": {}, "source": [ "* Líder en ciencia de datos. Experto 3.0\n", "* Matemático, informático y Estadístico, con Msc y PhD en Estadística.\n", "* Profesor de inteligencia artificial, minería de datos, aprendizaje profundo, métodos de computación intensiva ciencia de datos, big-data, estadística bayesiana, Teoría de Respuesta al Ítem, entre otras.\n", "* Desarrollado proyectos gubernamentales como el sistema de información ciencia y tecnología de Colombia.\n", "* Investigador y desarrollador en Inteligencia Artificial." ] }, { "cell_type": "markdown", "id": "b1f9c17d-9b94-4080-8518-6dac1fed7529", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "### Campo Elías Pardo, PhD" ] }, { "cell_type": "markdown", "id": "ab0d5617-b0c2-4cfc-ba3c-6658a759f780", "metadata": {}, "source": [ "* Experto en ciencia de datos. Experto 2.0\n", "* Ingeniero químico, con Msc y PhD en Estadística\n", "* Profesor de estadística multivariada Descriptiva, ciencia de datos, minería de datos, entre otros.\n", "* Desarrollo de productos de análisis multivariado de datos\n", "* Investigador y desarrollador en modelos no supervisados" ] }, { "cell_type": "markdown", "id": "aefd317f-cbe1-4570-95fc-ef0fd86e716c", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "### Daniel Montenegro, Msc" ] }, { "cell_type": "markdown", "id": "4221b944-5a46-47bd-b109-fd57ed31274d", "metadata": {}, "source": [ "* Experto en ciencia de datos. Experto 2.0\n", "* Matemático, con Msc y PhD en Matemática Aplicada\n", "* Profesor de inteligencia artificial, modelación matemática, métodos numéricos, redes neuronales, aprendizaje profundo, entre otros.\n", "* Desarrollo de proyecto de IA en lenguaje natural\n", "* Investigador y desarrollador en Inteligencia Artificial" ] }, { "cell_type": "markdown", "id": "0cb53d80-be40-46ec-9db1-218518a1bcbe", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "### Camilo Torres, Msc" ] }, { "cell_type": "markdown", "id": "9e90c9b6-2cba-4c90-8b15-eb062f27384b", "metadata": {}, "source": [ "* Experto en ciencia de datos. Experto 2.0.\n", "* Matemático, con línea de profundización en Informática y Msc en Estadística.\n", "* Profesor de cursos de fundamentación matemático-estadística, análisis de datos multivariados y lenguajes de programación, entre otros.\n", "* Programador, administrador de bases de datos (DBA), consultor y líder de proyectos en ciencia de datos." ] }, { "cell_type": "markdown", "id": "1cc01710-1c61-41e1-9f48-2c4620dd53f6", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "#
Que es la ciencia de datos
" ] }, { "cell_type": "markdown", "id": "1647d3b6-e922-40de-83ad-f4325fd5c454", "metadata": {}, "source": [ "**El área trabajo empresarial encargada de convertir datos en productos.**" ] }, { "cell_type": "markdown", "id": "72358432-cff3-4487-b792-b3d834a3ecda", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "
\n", "
\n", "\n", "
El quehacer de la ciencia de datos
\n", "
\n", "
" ] }, { "cell_type": "markdown", "id": "833f77bd-1588-46a9-89a8-1ac8d24d1a3e", "metadata": {}, "source": [ "## Identificar el problema y el objetivo" ] }, { "cell_type": "markdown", "id": "9ac81c4d-d0c7-49ee-9b48-0f0c079dff86", "metadata": {}, "source": [ "* **¿Cuál es el problema que quiero resolver?**\n", "\n", "* **¿Cuál es el objetivo?**\n", "\n", "* **¿Cuál es la meta a la que quiero llegar?**" ] }, { "cell_type": "markdown", "id": "4c449009-2c42-45e6-909e-1aa61f190cbb", "metadata": {}, "source": [ "## Capturar y recolectar de datos" ] }, { "cell_type": "markdown", "id": "931c4c35-b179-499b-ba8d-43df846bf3fd", "metadata": {}, "source": [ "Ejemplo de una \"encuesta\" en \"Google Forms\" (de pronto con serias debilidades...): [EncuestaInicioCurso.pdf](https://raw.githubusercontent.com/AprendizajeProfundo/diplomado-ciencia-de-datos/master/A_Preliminares/ArchivosOtros/EncuestaInicioCurso.pdf)\n", "\n", "Ejemplo de unos datos en una \"Hoja de cálculo\": [EncuestaInicioCursoResponses.xlsx](https://raw.githubusercontent.com/AprendizajeProfundo/diplomado-ciencia-de-datos/master/A_Preliminares/ArchivosOtros/EncuestaInicioCursoResponses.xlsx)" ] }, { "cell_type": "markdown", "id": "f6df3d88-c84b-46e3-a152-0fdb921abd53", "metadata": {}, "source": [ "## Transformar" ] }, { "cell_type": "markdown", "id": "54b7718e-1933-4a95-ba4b-ee955d7029f9", "metadata": {}, "source": [ "Ejemplo de unos datos en un archivo de texto plano `.csv` (del inglés *comma-separated values*, es decir, valores separados por comas): [EncuestaInicioCursoResponses.csv](https://raw.githubusercontent.com/AprendizajeProfundo/diplomado-ciencia-de-datos/master/A_Preliminares/ArchivosOtros/EncuestaInicioCursoResponses.csv)" ] }, { "cell_type": "code", "execution_count": 1, "id": "26952b19-cfca-4b63-91b6-6ec7f8748c1c", "metadata": {}, "outputs": [], "source": [ "#pip install pandas\n", "#conda install pandas\n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 2, "id": "31bf9a9a-a72a-4c4b-b0f5-68b132f9fd22", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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TimestampTXT_EXPECTATIVA_APRENDGRABAR_CLASESPROGRAMASEMESTRE_INICIONRO_MATRICULASPRCTJ_CRED_APROBPROP_CRED_APROBNRO_MATERIAS_INSCRNRO_CRED_INSCRHRS_TRABAJA_SEMANNIVEL_INGLESESTATURACAMBIO_PESO_DESEADOGENERO_BIO
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" ], "text/plain": [ " Timestamp TXT_EXPECTATIVA_APREND \\\n", "0 10/4/2021 13:01:19 Aprender sobre la estadística \n", "1 10/4/2021 13:06:59 Espero poder reforzar mis conocimientos sobre ... \n", "2 10/4/2021 13:07:40 Cosas útiles \n", "3 10/4/2021 13:13:26 Honestamente, cualquier conocimiento es bienve... \n", "4 10/4/2021 13:18:09 Pues aprender todo lo que se requiere en la ma... \n", "\n", " GRABAR_CLASES PROGRAMA SEMESTRE_INICIO NRO_MATRICULAS \\\n", "0 Sí Ingeniería Química 2020-I 4 \n", "1 Sí Contaduría pública 2020-II 3 \n", "2 Sí Ingeniería mecatrónica 2019-I 5 \n", "3 Sí Ingeniería Civil 2019-I 4 \n", "4 Sí Ingenieria civil 2019-I 6 \n", "\n", " PRCTJ_CRED_APROB PROP_CRED_APROB NRO_MATERIAS_INSCR NRO_CRED_INSCR \\\n", "0 35.0 56.00 5 17 \n", "1 15.0 1/7 3 9 \n", "2 10.0 1/10 5 19 \n", "3 20.0 36.00 6 20 \n", "4 35.0 75 créditos 5 16 \n", "\n", " HRS_TRABAJA_SEMAN NIVEL_INGLES ESTATURA CAMBIO_PESO_DESEADO GENERO_BIO \n", "0 50 B2 1.75 60.0 XY (Hombre) \n", "1 32 A2 1.68 -2.0 XY (Hombre) \n", "2 0 B2 1.73 0.0 XY (Hombre) \n", "3 16 B2 1.80 72.0 XY (Hombre) \n", "4 0 B1 1.70 2.0 XY (Hombre) " ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "url = \"https://raw.githubusercontent.com/AprendizajeProfundo/diplomado-ciencia-de-datos/master/\"\n", "carpetas = \"A_Preliminares/ArchivosOtros/\"\n", "archivo_csv = 'EncuestaInicioCursoResponses.csv'\n", "ruta_completa = archivo_csv\n", "datos = pd.read_csv(ruta_completa)\n", "datos.head()" ] }, { "cell_type": "markdown", "id": "1c99c3fd-9f22-4da0-9405-cce5d5fe63ee", "metadata": {}, "source": [ "* **¿Qué limpieza, depuración o transformaciones en general se requieren para este conjunto de datos? (el objetivo y las características de los datos guían la respuesta a esta pregunta)**" ] }, { "cell_type": "markdown", "id": "29b131aa-e7f5-4d14-b4bf-99f8532579ce", "metadata": {}, "source": [ "## Explorar, análizar, modelar, visualizar y concluir" ] }, { "cell_type": "markdown", "id": "f5f24203-9860-4ec5-ac82-19fa3685fd5a", "metadata": {}, "source": [ "* **¿Estadísticas básicas?**" ] }, { "cell_type": "code", "execution_count": 3, "id": "a5ff778c-8f63-4ba4-96b6-8ef58e36bbb8", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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NRO_MATRICULASPRCTJ_CRED_APROBNRO_MATERIAS_INSCRNRO_CRED_INSCRHRS_TRABAJA_SEMANESTATURACAMBIO_PESO_DESEADO
count47.00000047.00000047.00000047.00000047.00000047.00000047.000000
mean4.70212818.7744684.51063815.25531914.7021281.7221287.882979
std2.99212713.1613920.9972213.57812217.3667780.08350823.236780
min1.0000000.0000003.0000006.0000000.0000001.500000-20.000000
25%3.0000009.4500004.00000012.5000000.0000001.670000-2.500000
50%4.00000016.0000005.00000016.0000008.0000001.7300003.000000
75%5.00000026.5000005.00000018.00000025.0000001.78500010.000000
max18.00000056.4000007.00000021.00000050.0000001.85000075.000000
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" ], "text/plain": [ " NRO_MATRICULAS PRCTJ_CRED_APROB NRO_MATERIAS_INSCR NRO_CRED_INSCR \\\n", "count 47.000000 47.000000 47.000000 47.000000 \n", "mean 4.702128 18.774468 4.510638 15.255319 \n", "std 2.992127 13.161392 0.997221 3.578122 \n", "min 1.000000 0.000000 3.000000 6.000000 \n", "25% 3.000000 9.450000 4.000000 12.500000 \n", "50% 4.000000 16.000000 5.000000 16.000000 \n", "75% 5.000000 26.500000 5.000000 18.000000 \n", "max 18.000000 56.400000 7.000000 21.000000 \n", "\n", " HRS_TRABAJA_SEMAN ESTATURA CAMBIO_PESO_DESEADO \n", "count 47.000000 47.000000 47.000000 \n", "mean 14.702128 1.722128 7.882979 \n", "std 17.366778 0.083508 23.236780 \n", "min 0.000000 1.500000 -20.000000 \n", "25% 0.000000 1.670000 -2.500000 \n", "50% 8.000000 1.730000 3.000000 \n", "75% 25.000000 1.785000 10.000000 \n", "max 50.000000 1.850000 75.000000 " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "datos.describe()" ] }, { "cell_type": "markdown", "id": "942b1914-0784-4106-8ae0-08d3949087fe", "metadata": {}, "source": [ "* **¿Qué pasó con las demás variables?**" ] }, { "cell_type": "markdown", "id": "7278f49d-1313-497f-817e-35b5fdbab966", "metadata": {}, "source": [ "* **¿Gráficos?**" ] }, { "cell_type": "code", "execution_count": 4, "id": "17a62588-d071-40b2-8aa3-da0827e4ad91", "metadata": {}, "outputs": [], "source": [ "#pip install plotly\n", "#conda install plotly\n", "import plotly.express as px" ] }, { "cell_type": "code", "execution_count": 5, "id": "5f1823f7-0b76-4fd8-8417-6f5c2bc13699", "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "domain": { "x": [ 0, 1 ], "y": [ 0, 1 ] }, "hovertemplate": "NIVEL_INGLES=%{label}", "labels": [ "B2", "A2", "B2", "B2", "B1", "B1", "A1", "B2", "B1", "A1", "A1", "B2", "B1", "A2", "B1", "A2", "A1", "B2", "A2", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = px.scatter_3d(datos, x='HRS_TRABAJA_SEMAN', y='NRO_CRED_INSCR', z='NRO_MATERIAS_INSCR',\n", " size='NRO_MATRICULAS', color='PRCTJ_CRED_APROB', symbol='GENERO_BIO',\n", " symbol_sequence=['circle','square'], width=600, height=500)\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "34881289-40da-4eba-9e5b-1b681af92ffe", "metadata": {}, "source": [ "* **¿Qué métodos, técnicas, modelos debo aplicar? (el objetivo y las características de los datos guían la respuesta a esta pregunta)**" ] }, { "cell_type": "markdown", "id": "ea3d97cc-e3e3-4796-a732-9a8944ed1494", "metadata": {}, "source": [ "#
Claves de desarrollo en ciencia de datos
" ] }, { "cell_type": "markdown", "id": "f86d5d38-af80-4a75-ae52-e0ab4309f49b", "metadata": {}, "source": [ "
\n", "
\n", " \n", "
\n", "
" ] }, { "cell_type": "markdown", "id": "47815890-5b20-446c-95a4-af3eac8bc5a4", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "## Digitalización de documentos" ] }, { "cell_type": "markdown", "id": "5d714264-7b11-44b2-af9e-d54c8cbe5427", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "\n", "" ] }, { "cell_type": "markdown", "id": "657a10df-7d34-4c1e-81ea-89a2a5df816e", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "## Matemáticas" ] }, { "cell_type": "markdown", "id": "c31414ad-34cc-40fb-bf75-26b77520a8ec", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Tensores" ] }, { "cell_type": "markdown", "id": "5ed01eb5-f61c-4e11-bd02-603d7f479082", "metadata": {}, "source": [ "
\n", "\n", "
" ] }, { "cell_type": "markdown", "id": "13cdf148-30d1-44a7-a6c2-42c6d60016d2", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "
\n", "\n", "
" ] }, { "cell_type": "markdown", "id": "af0c0f34-f8dd-4187-b1bb-29860d634997", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Diferenciación Automática" ] }, { "cell_type": "markdown", "id": "7ccc7678-3f6a-443c-af6e-edf0e41c3b9e", "metadata": {}, "source": [ "
\n", "
\n", " \n", "
\n", "
" ] }, { "cell_type": "markdown", "id": "bf0dbf52-77ff-4923-b1d8-dee14709a25d", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Optimización a gran escala. Gradiente Estocástico Descendiente" ] }, { "cell_type": "markdown", "id": "064b01be-17d4-491f-b49f-d2c5edebee78", "metadata": {}, "source": [ "GPT-3, el moelo de lenguaje natural de OpenAI tiene 175 mil millones de parámetros." ] }, { "cell_type": "markdown", "id": "20d494a8-d5d7-4fd6-bfc9-053365d63c47", "metadata": {}, "source": [ "\n", "" ] }, { "cell_type": "markdown", "id": "efe4f270-4a54-4c8f-a0e7-9ae78b2a715a", "metadata": { "slideshow": { "slide_type": "skip" }, "tags": [] }, "source": [ "### Convoluciones" ] }, { "cell_type": "markdown", "id": "9548fb65-8226-4ea0-9a00-ce7324844428", "metadata": { "slideshow": { "slide_type": "skip" }, "tags": [] }, "source": [ "
\n", "
\n", " \n", "
\n", "
" ] }, { "cell_type": "markdown", "id": "33f23b8d-58e0-4450-afc6-9d7000758701", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Estadística" ] }, { "cell_type": "markdown", "id": "f4ae1656-e010-4d90-86c9-99d026092cef", "metadata": {}, "source": [ "![Digi1](https://raw.githubusercontent.com/AprendizajeProfundo/diplomado-ciencia-de-datos/master/A_Preliminares/Imagenes/mod_reg2.jpg)" ] }, { "cell_type": "markdown", "id": "98fd0bac-c4af-49d6-9b93-dfa1d35bba9a", "metadata": { "slideshow": { "slide_type": "subslide" }, "tags": [] }, "source": [ "![Clust](https://raw.githubusercontent.com/AprendizajeProfundo/diplomado-ciencia-de-datos/master/A_Preliminares/Imagenes/clustering.png)" ] }, { "cell_type": "markdown", "id": "d72c2ef2-e894-40ce-b977-89cf84d5e6af", "metadata": { "slideshow": { "slide_type": "subslide" }, "tags": [] }, "source": [ "![Clust2](https://raw.githubusercontent.com/AprendizajeProfundo/diplomado-ciencia-de-datos/master/A_Preliminares/Imagenes/clustering_2.png)" ] }, { "cell_type": "markdown", "id": "fd196ec7-9d91-436c-91a3-1c46e438d7f9", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Máquinas de Aprendizaje" ] }, { "cell_type": "markdown", "id": "861eb4c0-0d78-4cc4-bfe9-a1935934ce3d", "metadata": {}, "source": [ "![Digi1](https://raw.githubusercontent.com/AprendizajeProfundo/diplomado-ciencia-de-datos/master/A_Preliminares/Imagenes/mod_machine-learning-map.png)" ] }, { "cell_type": "markdown", "id": "1d11f99e-50fb-4689-8c50-4bfdd28b1e6c", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Red Neuronal" ] }, { "cell_type": "markdown", "id": "bf50dafe-8077-4a05-b37a-ece5a850889d", "metadata": {}, "source": [ "![Capa oculta](https://raw.githubusercontent.com/AprendizajeProfundo/diplomado-ciencia-de-datos/master/A_Preliminares/Imagenes/ANN_Capa_Oculta.png)" ] }, { "cell_type": "markdown", "id": "edc2269a-b321-433b-a7d1-d6df394c8d86", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "## Transformación de problemas" ] }, { "cell_type": "markdown", "id": "5b7676e7-71f0-4b1f-9bc9-8b7913aa305d", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Imagen a tensor" ] }, { "cell_type": "markdown", "id": "c3cf7ae9-44ba-4aec-83b5-c97bc0d0be84", "metadata": {}, "source": [ "
\n", "
\n", " \n", "
\n", "
" ] }, { "cell_type": "markdown", "id": "177ea86f-bf0f-4f16-b374-6a056dc6f10f", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Texto a tensor: Sumergimiento de palabras" ] }, { "cell_type": "markdown", "id": "2fff12c6-e0bf-41ce-aedd-c504d0ca91a1", "metadata": {}, "source": [ "
\n", "
\n", " \n", "
\n", "
" ] }, { "cell_type": "markdown", "id": "9bc2e4b3-e882-4a9e-a1ba-fe999195d906", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "## Tecnología" ] }, { "cell_type": "markdown", "id": "1f4fea4d-b6fb-4b87-a404-c4be09805f32", "metadata": { "slideshow": { "slide_type": "subslide" }, "tags": [] }, "source": [ "### Hardware tradicional : CPU, GPU" ] }, { "cell_type": "markdown", "id": "d79054d5-d9e0-4bc0-8e8b-584ce93f2b5f", "metadata": {}, "source": [ "\n", "" ] }, { "cell_type": "markdown", "id": "7993179f-05ad-4eb8-8326-41ad14f717b1", "metadata": { "slideshow": { "slide_type": "subslide" }, "tags": [] }, "source": [ "### Hardware moderno : TPU, Cerebras" ] }, { "cell_type": "markdown", "id": "808ea59c-3aa2-4576-b445-b3904f952db1", "metadata": {}, "source": [ "
\n", "\n", "
\n", "
\n", "\n", "
" ] }, { "cell_type": "markdown", "id": "c1ce7a23-cd15-4a38-9897-d6bb39fd02d8", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Computación en la nube" ] }, { "cell_type": "markdown", "id": "ecddd2c9-3c3b-4162-8d45-d7ff2fc7773c", "metadata": {}, "source": [ "
\n", "
\n", " \n", "
\n", "
" ] }, { "cell_type": "markdown", "id": "eb1c7c34-106b-4d62-9b6d-af236b76c3e1", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Big data" ] }, { "cell_type": "markdown", "id": "08a02cb6-93d8-4763-9ae6-a82d2be92491", "metadata": {}, "source": [ "
\n", "
\n", " \n", "
\n", "
" ] }, { "cell_type": "markdown", "id": "db3d50c6-bf2b-4b4d-b135-6050092d6ad1", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Programación: ciencia de datos, redes neuronales" ] }, { "cell_type": "markdown", "id": "7570b6c2-8b9b-48bd-a5d2-1f764e5b04b1", "metadata": {}, "source": [ "
\n", "
\n", " \n", "
\n", "
" ] }, { "cell_type": "markdown", "id": "fc52ce75-03df-4fc8-bf2b-5775ddf039b8", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "## Arquitecturas Neuronales Paradigma" ] }, { "cell_type": "markdown", "id": "8f6b31d6-72e3-4322-b21c-21e9120a0cdc", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Modelo Convolucional" ] }, { "cell_type": "markdown", "id": "c573dab4-fda2-43a5-8f1c-952ca3f82428", "metadata": {}, "source": [ "![](https://raw.githubusercontent.com/AprendizajeProfundo/diplomado-ciencia-de-datos/master/A_Preliminares/Imagenes/cnn-procedure.png)" ] }, { "cell_type": "markdown", "id": "5c52a6fa-8709-4fbf-b52a-2f3afd425699", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Modelo Recurrente" ] }, { "cell_type": "markdown", "id": "0f67afdc-2b50-4f76-8a92-da7450c02f73", "metadata": {}, "source": [ "![](https://raw.githubusercontent.com/AprendizajeProfundo/diplomado-ciencia-de-datos/master/A_Preliminares/Imagenes/RNN-longtermdependencies.png)" ] }, { "cell_type": "markdown", "id": "c7039faa-340a-4270-8153-b4121109e689", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Modelo Atencional: Transformers" ] }, { "cell_type": "markdown", "id": "536b6f04-411f-41f1-a7a5-9e84aa5c3644", "metadata": {}, "source": [ "
\n", "
\n", " \n", "
\n", "
" ] }, { "cell_type": "markdown", "id": "9c497ecc-19f8-4cf7-8471-f7a8ea980152", "metadata": { "slideshow": { "slide_type": "slide" }, "tags": [] }, "source": [ "### Transferencia de conocimiento" ] }, { "cell_type": "markdown", "id": "ee6206fb-282c-449d-99ef-0cbcbf88b808", "metadata": {}, "source": [ "
\n", "
\n", " \n", "
\n", "
\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.6" } }, "nbformat": 4, "nbformat_minor": 5 }