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Subject: [PATCH 2/2] add readme --- awesome/README.ipynb | 156 +++++++++++++++++++++---------------------- 1 file changed, 76 insertions(+), 80 deletions(-) diff --git a/awesome/README.ipynb b/awesome/README.ipynb index 28cdf33d78..6c093421fb 100644 --- a/awesome/README.ipynb +++ b/awesome/README.ipynb @@ -2,26 +2,13 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 47, "metadata": { "tags": [ "remove_cell" ] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", - "jupyterlab-server 2.12.0 requires jupyter-server~=1.8, but you have jupyter-server 2.6.0 which is incompatible.\n", - "nbclassic 0.3.5 requires jupyter-server~=1.8, but you have jupyter-server 2.6.0 which is incompatible.\u001b[0m\u001b[31m\n", - "\u001b[0m\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.1.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n" - ] - } - ], + "outputs": [], "source": [ "# Install the necessary dependencies\n", "\n", @@ -52,7 +39,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 48, "metadata": {}, "outputs": [], "source": [ @@ -79,72 +66,81 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "| | Title | Author | Organization | Topic | Price | Level | Type | Hascert | Language | Tag |\n", - "|---:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------|:--------------------|:---------------|:----------------|:--------------|:----------|:-----------------------|:--------------------------------------------------------------------------------------------------|\n", - "| 1 | Data Visualization | | freeCodeCamp | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿ“ˆ Data visualization ๐Ÿซ™ Javascript ๐Ÿ‘จโ€๐Ÿซ Projects |\n", - "| 2 | Relational Database | | freeCodeCamp | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿ“Š SQL |\n", - "| 3 | Scientific Computing with Python | Charles Severance | freeCodeCamp | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿ Python ๐ŸŽฅ Video |\n", - "| 4 | Data Analysis with Python | Santiago Basulto | freeCodeCamp | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿ Python ๐ŸŽฅ Video |\n", - "| 5 | Machine Learning with Python | Tim Ruscica | freeCodeCamp | ๐Ÿค– AI | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning |\n", - "| 6 | Big Data, Large Scale Machine Learning | John Langford, Yann LeCun | New York University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning โšก๏ธ Big data |\n", - "| 7 | Artificial Intelligence | Patrick Henry Winston | MIT | ๐Ÿค– AI | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿค– AI |\n", - "| 8 | Natural Language Processing with Deep Learning | Chris Manning | Stanford | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿ‘ฝ Deep learning ๐Ÿ—ฃ๏ธ NLP |\n", - "| 9 | Machine Learning: 2014-2015 | Nando de Freitas | Oxford | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning |\n", - "| 10 | Getting Started with Deep Learning | | NVIDIA | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฅ Paid of 90$ | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning โšก๏ธ Big data ๐Ÿ‘ฝ Deep learning ๐Ÿ‘“ Computer vision |\n", - "| 11 | Building Video AI Applications at the Edge on Jetson Nano | | NVIDIA | ๐Ÿฆฟ Robotics | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ‘“ Computer vision |\n", - "| 12 | Getting Started with AI on Jetson Nano | | NVIDIA | ๐Ÿฆฟ Robotics | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘“ Computer vision ๐Ÿ’ป Hardware ๐Ÿฆฟ Robotics |\n", - "| 13 | Graduate Summer School: Deep Learning, Feature Learning | Yann LeCun, Yoshua Bengio, Geoffrey Hinton, Andrew Ng, Stanley Osher | UCLA | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 14 | Deep Learning 2017 | Ali Ghodsi | University of Waterloo | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 15 | Deep Learning | Ali Ghodsi | University of Waterloo | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 16 | Statistical Machine Learning: Spring 2017 | Ryan Tibshirani, Larry Wasserman | Carnegie Mellon University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning |\n", - "| 17 | UVA Deep Learning Course | Yuki Asano | University of Amsterdam | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 18 | MIT Deep Learning and Artificial Intelligence Lectures | Lex Fridman | MIT | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿš— Self driving |\n", - "| 19 | Introduction to Deep Learning | Alexander Amini & Ava Amini & Sadhana Lolla | MIT | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 20 | Deep Reinforcement Learning | Sergey Levine | UC Berkeley | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 21 | Practical Deep Learning | Jeremy Howard | | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 22 | Introduction to Deep Learning | Bhiksha Raj, Rita Singh | Carnegie Mellon University | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 23 | AI for Everyone | Andrew Ng | | ๐Ÿค– AI | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿค– AI ๐Ÿ‘ฝ Deep learning |\n", - "| 24 | Yann LeCunโ€™s Deep Learning Course at CDS | Yann LeCun | New York University | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English ๐Ÿ‡ซ๐Ÿ‡ท franรงais | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 25 | Neural Networks and Deep Learning | Alan Blair | University of New South Wales | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 26 | Spinning Up in Deep Reinforcement Learning | Josh Achiam | | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐ŸŽฎ Reinforcement learning |\n", - "| | | | | | | | | | | |\n", - "| 27 | Introduction to Deep Learning | Alex Smola, Mu Li | UC Berkeley | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 28 | Dive into Deep Learning in 1 Day | Alex Smola | ODSC | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 29 | Dive into Deep Learning | Rachel Hu, Aston Zhang | GTC | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 30 | ๅŠจๆ‰‹ๅญฆๆทฑๅบฆๅญฆไน ๅœจ็บฟ่ฏพ็จ‹ | Mu Li | D2L | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡จ๐Ÿ‡ณ ไธญๆ–‡ | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 31 | Practical Machine Learning | Alex Smola, Mu Li | | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 32 | Learning from Data | Yaser Abu-Mostafa | Caltech | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐ŸŽฅ Video ๐Ÿง  Machine learning โšก๏ธ Big data |\n", - "| 33 | Computational Systems Biology: Deep Learning in the Life Sciences | Manolis Kellis | MIT | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ“ˆ Data visualization ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 34 | Introduction to Deep Learning and Generative Models | Sebastian Raschka | UNIVERSITY OF WISCONSINโ€“MADISON | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 35 | Deep Learning for Speech and Language | Antonio Bonafonte &\tJose Adriรกn Rodrรญguez Fonollosa &\tMarta Ruiz Costa-jussร  \t& Javier Hernando \t& Santiago Pascual \t& Elisa Sayrol \t& Xavier Giro-i-Nieto | Universitat Politรจcnica de Catalunya | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ—ฃ๏ธ NLP |\n", - "| 36 | Deep Learning on Computational Accelerators | Alex Bronstein & Chaim Baskin & Moshe Kimhi & Mitchell Keren Taraday | Technion | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", - "| 37 | Applications of Deep Neural Networks | Jeff Heaton | Washington University in St. Louis | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ‘ฝ Deep learning |\n", - "| 38 | Introduction to Deep Learning | Alexander Amini & Ava Amini & Sadhana Lolla | MIT | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ—ฃ๏ธ NLP ๐Ÿ‘“ Computer vision |\n", - "| 39 | Deep Learning | Justin Sirignano | Univ. of Illinois at Urbana-Champaign | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ—ฃ๏ธ NLP |\n", - "| 40 | Deep learning course | Victor Lempitsky | Skoltech | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English ๐Ÿ‡ท๐Ÿ‡บ ั€ัƒััะบะธะน | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ—ฃ๏ธ NLP |\n", - "| 41 | Deep Learning for Natural Language Processing | Phil Blunsom | Oxford | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿง  Machine learning |\n", - "| 42 | Machine Learning | Tony Jebara | Columbia University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿง  Machine learning |\n", - "| 43 | Harvard University: Introduction to Data Science with Python | Pavlos Protopapas | Havard University | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿง  Machine learning |\n", - "| 44 | Introduction to Machine Learning | Jennifer Listgarten, Jitendra Malik | UC Berkeley | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿง  Machine learning |\n", - "| 45 | Natural Language Processing with Deep Learning | Christopher Manning | Stanford | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |\n", - "| 46 | Deep Learning for Computer Vision | Fei-Fei Li, Yunzhu Li, Ruohan Gao | Stanford | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |\n", - "| 47 | Advanced Robotics | Pieter Abbeel | UC Berkeley | ๐Ÿฆฟ Robotics | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿฆฟ Robotics |\n", - "| 48 | Machine Learning | Thorsten Joachims | Cornell University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿง  Machine learning |\n", - "| 49 | Machine Learning for Data Science | Lillian Lee | Cornell University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿง  Machine learning |\n", - "| 50 | Deep Learning | | New York University | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |\n", - "| 51 | Deep Learning for Computer Vision and Natural Language Processing | Liangliang Cao, Dr. James Fan | Columbia University | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |\n", - "| 52 | Introduction to Matrix Methods | John C. Duchi | Stanford | ๐Ÿ Python | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿงฎ Math |\n", - "| 53 | Machine Learning | Tom Mitchell | Carnegie Mellon University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿง  Machine learning |\n", - "| 54 | Introduction to Deep Learning | Bhiksha Raj | Carnegie Mellon University | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |\n", - "| 55 | Mining Massive Data Sets | Jure Leskovec, Mina Ghashami | Stanford | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science |\n", - "| 56 | Reinforcement Learning in the Wild | | | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐ŸŽฎ Reinforcement learning |\n", - "| 57 | UVA DEEP LEARNING COURSE | Yuki Asano | | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |" + "| | Title | Author | Organization | Topic | Price | Level | Type | Hascert | Language | Tag |\n", + "|---:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------|:--------------------|:---------------|:----------------|:--------------|:----------|:-----------------------|:--------------------------------------------------------------------------------------------------|\n", + "| 1 | Data Visualization | | freeCodeCamp | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿ“ˆ Data visualization ๐Ÿซ™ Javascript ๐Ÿ‘จโ€๐Ÿซ Projects |\n", + "| 2 | Relational Database | | freeCodeCamp | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿ“Š SQL |\n", + "| 3 | Scientific Computing with Python | Charles Severance | freeCodeCamp | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿ Python ๐ŸŽฅ Video |\n", + "| 4 | Data Analysis with Python | Santiago Basulto | freeCodeCamp | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿ Python ๐ŸŽฅ Video |\n", + "| 5 | Machine Learning with Python | Tim Ruscica | freeCodeCamp | ๐Ÿค– AI | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning |\n", + "| 6 | Big Data, Large Scale Machine Learning | John Langford, Yann LeCun | New York University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning โšก๏ธ Big data |\n", + "| 7 | Artificial Intelligence | Patrick Henry Winston | MIT | ๐Ÿค– AI | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿค– AI |\n", + "| 8 | Natural Language Processing with Deep Learning | Chris Manning | Stanford | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿ‘ฝ Deep learning ๐Ÿ—ฃ๏ธ NLP |\n", + "| 9 | Machine Learning: 2014-2015 | Nando de Freitas | Oxford | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning |\n", + "| 10 | Getting Started with Deep Learning | | NVIDIA | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฅ Paid of 90$ | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning โšก๏ธ Big data ๐Ÿ‘ฝ Deep learning ๐Ÿ‘“ Computer vision |\n", + "| 11 | Building Video AI Applications at the Edge on Jetson Nano | | NVIDIA | ๐Ÿฆฟ Robotics | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ‘“ Computer vision |\n", + "| 12 | Getting Started with AI on Jetson Nano | | NVIDIA | ๐Ÿฆฟ Robotics | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘“ Computer vision ๐Ÿ’ป Hardware ๐Ÿฆฟ Robotics |\n", + "| 13 | Graduate Summer School: Deep Learning, Feature Learning | Yann LeCun, Yoshua Bengio, Geoffrey Hinton, Andrew Ng, Stanley Osher | UCLA | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 14 | Deep Learning 2017 | Ali Ghodsi | University of Waterloo | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 15 | Deep Learning | Ali Ghodsi | University of Waterloo | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 16 | Statistical Machine Learning: Spring 2017 | Ryan Tibshirani, Larry Wasserman | Carnegie Mellon University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning |\n", + "| 17 | UVA Deep Learning Course | Yuki Asano | University of Amsterdam | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 18 | MIT Deep Learning and Artificial Intelligence Lectures | Lex Fridman | MIT | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿš— Self driving |\n", + "| 19 | Introduction to Deep Learning | Alexander Amini & Ava Amini & Sadhana Lolla | MIT | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 20 | Deep Reinforcement Learning | Sergey Levine | UC Berkeley | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 21 | Practical Deep Learning | Jeremy Howard | | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 22 | Introduction to Deep Learning | Bhiksha Raj, Rita Singh | Carnegie Mellon University | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 23 | AI for Everyone | Andrew Ng | | ๐Ÿค– AI | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿค– AI ๐Ÿ‘ฝ Deep learning |\n", + "| 24 | Yann LeCunโ€™s Deep Learning Course at CDS | Yann LeCun | New York University | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English ๐Ÿ‡ซ๐Ÿ‡ท franรงais | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 25 | Neural Networks and Deep Learning | Alan Blair | University of New South Wales | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 26 | Spinning Up in Deep Reinforcement Learning | Josh Achiam | | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐ŸŽฎ Reinforcement learning |\n", + "| | | | | | | | | | | |\n", + "| 27 | Introduction to Deep Learning | Alex Smola, Mu Li | UC Berkeley | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 28 | Dive into Deep Learning in 1 Day | Alex Smola | ODSC | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 29 | Dive into Deep Learning | Rachel Hu, Aston Zhang | GTC | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 30 | ๅŠจๆ‰‹ๅญฆๆทฑๅบฆๅญฆไน ๅœจ็บฟ่ฏพ็จ‹ | Mu Li | D2L | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡จ๐Ÿ‡ณ ไธญๆ–‡ | ๐Ÿ‘จโ€๐Ÿซ Projects ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 31 | Practical Machine Learning | Alex Smola, Mu Li | | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘จโ€๐Ÿซ Projects ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 32 | Learning from Data | Yaser Abu-Mostafa | Caltech | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐ŸŽฅ Video ๐Ÿง  Machine learning โšก๏ธ Big data |\n", + "| 33 | Computational Systems Biology: Deep Learning in the Life Sciences | Manolis Kellis | MIT | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ“ˆ Data visualization ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 34 | Introduction to Deep Learning and Generative Models | Sebastian Raschka | UNIVERSITY OF WISCONSINโ€“MADISON | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 35 | Deep Learning for Speech and Language | Antonio Bonafonte &\tJose Adriรกn Rodrรญguez Fonollosa &\tMarta Ruiz Costa-jussร  \t& Javier Hernando \t& Santiago Pascual \t& Elisa Sayrol \t& Xavier Giro-i-Nieto | Universitat Politรจcnica de Catalunya | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ—ฃ๏ธ NLP |\n", + "| 36 | Deep Learning on Computational Accelerators | Alex Bronstein & Chaim Baskin & Moshe Kimhi & Mitchell Keren Taraday | Technion | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning |\n", + "| 37 | Applications of Deep Neural Networks | Jeff Heaton | Washington University in St. Louis | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ‘ฝ Deep learning |\n", + "| 38 | Introduction to Deep Learning | Alexander Amini & Ava Amini & Sadhana Lolla | MIT | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ—ฃ๏ธ NLP ๐Ÿ‘“ Computer vision |\n", + "| 39 | Deep Learning | Justin Sirignano | Univ. of Illinois at Urbana-Champaign | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ—ฃ๏ธ NLP |\n", + "| 40 | Deep learning course | Victor Lempitsky | Skoltech | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English ๐Ÿ‡ท๐Ÿ‡บ ั€ัƒััะบะธะน | ๐Ÿ Python ๐ŸŽฅ Video ๐Ÿง  Machine learning ๐Ÿ‘ฝ Deep learning ๐Ÿ—ฃ๏ธ NLP |\n", + "| 41 | Deep Learning for Natural Language Processing | Phil Blunsom | Oxford | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿง  Machine learning |\n", + "| 42 | Machine Learning | Tony Jebara | Columbia University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿง  Machine learning |\n", + "| 43 | Harvard University: Introduction to Data Science with Python | Pavlos Protopapas | Havard University | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿง  Machine learning |\n", + "| 44 | Introduction to Machine Learning | Jennifer Listgarten, Jitendra Malik | UC Berkeley | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿง  Machine learning |\n", + "| 45 | Natural Language Processing with Deep Learning | Christopher Manning | Stanford | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |\n", + "| 46 | Deep Learning for Computer Vision | Fei-Fei Li, Yunzhu Li, Ruohan Gao | Stanford | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |\n", + "| 47 | Advanced Robotics | Pieter Abbeel | UC Berkeley | ๐Ÿฆฟ Robotics | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿฆฟ Robotics |\n", + "| 48 | Machine Learning | Thorsten Joachims | Cornell University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿง  Machine learning |\n", + "| 49 | Machine Learning for Data Science | Lillian Lee | Cornell University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿง  Machine learning |\n", + "| 50 | Deep Learning | | New York University | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |\n", + "| 51 | Deep Learning for Computer Vision and Natural Language Processing | Liangliang Cao, Dr. James Fan | Columbia University | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |\n", + "| 52 | Introduction to Matrix Methods | John C. Duchi | Stanford | ๐Ÿ Python | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿงฎ Math |\n", + "| 53 | Machine Learning | Tom Mitchell | Carnegie Mellon University | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿง  Machine learning |\n", + "| 54 | Introduction to Deep Learning | Bhiksha Raj | Carnegie Mellon University | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |\n", + "| 55 | Mining Massive Data Sets | Jure Leskovec, Mina Ghashami | Stanford | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸง Intermediate | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science |\n", + "| 56 | Reinforcement Learning in the Wild | | | ๐Ÿ’ฟ Data science | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐ŸŽฎ Reinforcement learning |\n", + "| 57 | UVA DEEP LEARNING COURSE | Yuki Asano | | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ‘ฝ Deep learning |\n", + "| 58 | Machine Learning for Beginners | Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura | Microsoft | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ’ฟ Data science ๐Ÿ Python |\n", + "| 59 | Machine Learning Crash Course with TensorFlow APIs | | Google for Developers | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐ŸŽฅ Video ๐Ÿง  Machine learning |\n", + "| 60 | Deep Learning course | Charles Ollion, Olivier Grisel | Institut polytechnique de Paris | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English ๐Ÿ‡ซ๐Ÿ‡ท franรงais | ๐Ÿ Python ๐Ÿ‘ฝ Deep learning |\n", + "| 61 | Full Stack Deep Learning | | | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฅ Advanced | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐Ÿ‘ฝ Deep learning |\n", + "| 62 | mlcourse.ai โ€“ Open Machine Learning Course | | | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐Ÿง  Machine learning |\n", + "| 63 | Deep Learning Using PyTorch | Hossein Hajiabolhassan | | ๐Ÿ‘ฝ Deep learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐Ÿ‘ฝ Deep learning |\n", + "| 64 | A Machine Learning Course with Python | Amirsina Torfi | | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿง  Machine learning |\n", + "| 65 | MLOps Zoomcamp | Alexey Grigorev | | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English | ๐Ÿ Python ๐Ÿง  Machine learning |\n", + "| 66 | Machine Learning course | Vladislav Goncharenko, Radoslav Neychev | MIPT | ๐Ÿง  Machine learning | ๐ŸŸฉ Free | ๐ŸŸฉ Beginner | ๐ŸŸฉ Self-paced | โŒ | ๐Ÿ‡บ๐Ÿ‡ธ English ๐Ÿ‡ท๐Ÿ‡บ ั€ัƒััะบะธะน | ๐Ÿ Python ๐Ÿง  Machine learning |" ], "text/plain": [ "" @@ -185,7 +181,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 50, "metadata": { "tags": [ "remove_cell" @@ -193,7 +189,7 @@ }, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ "[NbConvertApp] Converting notebook README.ipynb to markdown\n", @@ -224,7 +220,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.5" + "version": "3.9.16" } }, "nbformat": 4,