On demand: The 2021 Amazon Machine Learning Summit

{"value":"Amazon Web Services (Amazon Web Services) held a[ free virtual Machine Learning Summit](https://amzn.to/32Bhxp8) on June 2, with the goal of bringing together customers, developers, and the science community to learn about advances in the practice of machine learning (ML).\n\n#### **Opening keynote**\n\nThe event began with a keynote from from [Swami Sivasubramanian](https://www.amazon.science/latest-news/swami-sivasubramanian-machine-learning-is-one-of-the-most-disruptive-technologies-we-will-encounter-in-our-generation), Amazon Web Services vice president of machine learning; [Bratin Saha](https://www.linkedin.com/in/bratin-saha-05824b3/), vice president of Amazon Web Services Machine Learning Services; and [Yoelle Maarek](https://www.amazon.science/author/yoelle-maarek), vice president of research science, Alexa Shopping.\n\n**Amazon Web Services ML Summit 2021 | Opening Keynote**\n\n#### **Fireside chat**\n\nNext up was a fireside chat. [Andrew Ng](https://www.linkedin.com/in/andrewyng/), founder and CEO of Landing AI, and Sivasubramanian discussed the future of ML, the skills that are fundamental for the next generation of ML practitioners, and how to bridge the proof-of-concept-to-production gap in ML.\n\n**Amazon Web Services ML Summit 2021 | Fireside Chat**\n\n#### **Breakout sessions**\n\nhe Summit included four audience-focused tracks which ran throughout the day:\n\n- Science of Machine Learning;\n- Impact of Machine Learning;\n- How Machine Learning Is Done; and\n- Machine Learning — No Experience Required\n\n#### **Science of Machine Learning track fireside chat**\n\nThe Science of Machine Learning track comprised six 30-minute presentations, and a fireside chat on deep learning and language with Amazon distinguished scientists [Alex Smola](https://www.amazon.science/author/alex-smola) and [Bernhard Schölkopf](https://www.amazon.science/author/bernhard-scholkopf), and Alexa AI senior principal scientist [Dilek Hakkani-Tur](https://www.amazon.science/author/dilek-hakkani-tur).\n\n**Machine Learning track fireside chat replay: Causality, robustness, and natural language understanding in ML**\n\n#### **Science of Machine Learning track session videos and interviews**\n\nBelow are video replays from each of the speakers in the Science of Machine Learning track, along with links to interviews Amazon Science did with each of the speakers in the weeks before the summit. [Click here to see the full list of ML Summit videos](https://www.youtube.com/playlist?list=PL2yQDdvlhXf9pBU8bAO_EseecE4_jaYZb).\n\n**Marzia Polito replay: Building high-quality computer vision models using only a few examples**\n\n\nABOUT THE AUTHOR\n\n#### **Staff writer**\n\n","render":"<p>Amazon Web Services (Amazon Web Services) held a<a href=\\"https://amzn.to/32Bhxp8\\" target=\\"_blank\\"> free virtual Machine Learning Summit</a> on June 2, with the goal of bringing together customers, developers, and the science community to learn about advances in the practice of machine learning (ML).</p>\\n<h4><a id=\\"Opening_keynote_2\\"></a><strong>Opening keynote</strong></h4>\\n<p>The event began with a keynote from from <a href=\\"https://www.amazon.science/latest-news/swami-sivasubramanian-machine-learning-is-one-of-the-most-disruptive-technologies-we-will-encounter-in-our-generation\\" target=\\"_blank\\">Swami Sivasubramanian</a>, Amazon Web Services vice president of machine learning; <a href=\\"https://www.linkedin.com/in/bratin-saha-05824b3/\\" target=\\"_blank\\">Bratin Saha</a>, vice president of Amazon Web Services Machine Learning Services; and <a href=\\"https://www.amazon.science/author/yoelle-maarek\\" target=\\"_blank\\">Yoelle Maarek</a>, vice president of research science, Alexa Shopping.</p>\\n<p><strong>Amazon Web Services ML Summit 2021 | Opening Keynote</strong></p>\\n<h4><a id=\\"Fireside_chat_8\\"></a><strong>Fireside chat</strong></h4>\\n<p>Next up was a fireside chat. <a href=\\"https://www.linkedin.com/in/andrewyng/\\" target=\\"_blank\\">Andrew Ng</a>, founder and CEO of Landing AI, and Sivasubramanian discussed the future of ML, the skills that are fundamental for the next generation of ML practitioners, and how to bridge the proof-of-concept-to-production gap in ML.</p>\\n<p><strong>Amazon Web Services ML Summit 2021 | Fireside Chat</strong></p>\\n<h4><a id=\\"Breakout_sessions_14\\"></a><strong>Breakout sessions</strong></h4>\\n<p>he Summit included four audience-focused tracks which ran throughout the day:</p>\n<ul>\\n<li>Science of Machine Learning;</li>\n<li>Impact of Machine Learning;</li>\n<li>How Machine Learning Is Done; and</li>\n<li>Machine Learning — No Experience Required</li>\n</ul>\\n<h4><a id=\\"Science_of_Machine_Learning_track_fireside_chat_23\\"></a><strong>Science of Machine Learning track fireside chat</strong></h4>\\n<p>The Science of Machine Learning track comprised six 30-minute presentations, and a fireside chat on deep learning and language with Amazon distinguished scientists <a href=\\"https://www.amazon.science/author/alex-smola\\" target=\\"_blank\\">Alex Smola</a> and <a href=\\"https://www.amazon.science/author/bernhard-scholkopf\\" target=\\"_blank\\">Bernhard Schölkopf</a>, and Alexa AI senior principal scientist <a href=\\"https://www.amazon.science/author/dilek-hakkani-tur\\" target=\\"_blank\\">Dilek Hakkani-Tur</a>.</p>\\n<p><strong>Machine Learning track fireside chat replay: Causality, robustness, and natural language understanding in ML</strong></p>\\n<h4><a id=\\"Science_of_Machine_Learning_track_session_videos_and_interviews_29\\"></a><strong>Science of Machine Learning track session videos and interviews</strong></h4>\\n<p>Below are video replays from each of the speakers in the Science of Machine Learning track, along with links to interviews Amazon Science did with each of the speakers in the weeks before the summit. <a href=\\"https://www.youtube.com/playlist?list=PL2yQDdvlhXf9pBU8bAO_EseecE4_jaYZb\\" target=\\"_blank\\">Click here to see the full list of ML Summit videos</a>.</p>\\n<p><strong>Marzia Polito replay: Building high-quality computer vision models using only a few examples</strong></p>\\n<p>ABOUT THE AUTHOR</p>\n<h4><a id=\\"Staff_writer_38\\"></a><strong>Staff writer</strong></h4>\n"}