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Are you interested in exploring and experimenting with Generative AI and Large-Language Models, or brushing up on your deep learning fundamentals? If so, look no further than our weekly study groups! Our Generative AI Study Group meets every Friday at 8am PST. The group focuses on exploring practical applications of generative models. We'll dig into a variety of topics, including fine-tuning, hosting LLMs, effective prompting techniques, and utilizing task-specific models like BERT to enhance an LLM-centric approach. We'll also discuss useful tools, plugins, agents, and build the TWIML-RAG, a TWIML podcast dialog application. Whether you’re an established LLM practitioner or are simply curious, this study group is the perfect platform to explore, learn, and share experiences with co-LLM enthusiasts. This study group is open to anyone and we encourage you to join in and share this with your friends and colleagues who you think might find this interesting. Watch out for this study group every Friday at 8am PST and join the #generative-ai Slack channel for more details and updates. Another recently-started group is working through Part 2 of Fast.ai’s Practical Deep Learning for Coders (Part 2) course. The Practical DL 2 Study Group will explore diffusion methods, implement unconditional and conditional diffusion models, experiment with different samplers, and dive into recent tricks like textual inversion and Dreambooth. Along the way, participants will also cover essential deep learning topics and get their hands dirty by building models from scratch, including Multi-Layer Perceptrons (MLPs), ResNets, and Unets, as well as generative architectures like autoencoders and transformers. For this study group, we’d recommend completing the Practical Deep Learning course Part 1 first, but if you are comfortable with building an SGD training loop from scratch in Python, being competitive in Kaggle competitions, using modern NLP and computer vision algorithms for practical problems, and working with PyTorch and fastai, then you will be ready to jump into the course. For those who want to participate in this study group, the meetup is every Saturday 8am PST and the Slack channel is #practical-dl-for-coders-part-2. Remember to register at the TWIML Community Page to join these awesome study groups! That’s a wrap! We hope you found something of interest and we hope our community can serve as a bridge for you to connect and embark on a learning journey with like-minded individuals.
One of the silver linings to an otherwise crazy year was that I spent a lot of time at a desk that would have otherwise been spent in planes, trains, and automobiles. As a result, Team TWIML got quite a lot done this year! I thought I’d share a few of the accomplishments we’re most proud of this year. Expansion of Our Education & Community Programs Thinking back to our team retreat in January (good times!) a big part of what we wanted to accomplish this year was to broaden our education and community offerings and to further the vision of the TWIML Community as a place for those interested in ML and AI to advance their skills and knowledge. In January we partnered with instructor Robert Ness to launch his Causal Modeling in Machine Learning course to rave reviews. We’ve since delivered it to two additional cohorts, and we’re super excited to work with Robert to launch two new courses in January. We also worked with Luigi Patruno to launch his first course on Amazon SageMaker this year. Our community stepped up in a big way this year as well. This year we held more study groups than ever— sixteen in total—including standbys like the Fast.ai Practical Deep Learning for Coders course that we’ve run for several years now, as well as a host of new offerings like the aforementioned AI Enterprise Workflow group, and groups focused on topics like Deep Reinforcement Learning, Natural Language Processing, Kaggle, and more. Leaning into Video Early on in the pandemic, we realized that folks would be spending a lot more time in front of their computers than usual, and we decided to help them take advantage of this opportunity by leaning into video. We started with our first video interview back in April (Google’s Quoc Le) and at this point, I can’t remember the last audio-only interview I’ve done. We also added online panel discussions to our regular repertoire this year. In an effort to support our community during the pandemic we took on subjects like Responsible Data Science in the Fight Against COVID-19, and Advancing Your Data Science Career During the Pandemic. We’ve since broadened our coverage to include practical and technical topics like the ML Programming Language Un-Debate, the Model Explainability Forum, and Feature Stores for Accelerating AI Development. If you missed any of these, you can watch them on our YouTube channel. Please take a moment to subscribe here! TWIMLfest: A Virtual AI Festival We were really inspired by our community this year, and the passion and zeal they continued to bring to the study and advancement of ML and AI, even during a pandemic. To celebrate them and their accomplishments, we launched TWIMLfest, a global celebration of the TWIML Community. TWIMLfest was a virtual festival spanning three weeks, dedicated to connection, collaboration, fun, and learning. While we originally envisioned something much smaller, the event ultimately spanned 3 weeks and offered 40 sessions, hosted 70+ speakers, and saw over 1,700 members of our community register! Some of the highlights include my keynote Interview with Sal Khan, the panel discussion on Accessibility and Computer Vision, and the Coded Bias Film Screening + Director Q&A. Stacking the Bricks In addition to these programs, we also laid the groundwork for a lot of exciting work that will come to fruition in early 2021, including our AI Solutions Guide and the TWIMLcon conference, and we’re within spitting distance of achieving 10 million downloads, a milestone we expect to hit early next year. We’ve also been working behind the scenes to fine-tune a lot of what we do as a company, an ongoing effort that will allow us to elevate our for ML/AI programming and events once again. We can’t wait to see you all in 2021! From the entire TWIML team, we wish you happy holidays as we celebrate the end of this wild year. Cheers! Sam
TWIML x Fast.ai Practical Deep Learning for Coders Study Groups NEW: June – November ’19: Stanford CS224n On Saturday, June 22nd we launched a CS224n study group covering the Stanford CS224n: Natural Language Processing with Deep Learning course. This study group will meet weekly on Saturdays at 10 am Pacific Time until November 9th, each week covering a new lesson from the course. After a vote and some discussion by our current study group community members, this was the course that came out on top. Learn more about this course and the topics covered here. The 4th Cohort: June – October ’19: Deep Learning for Coders Part 2 Back by popular demand, we’ve rebooted a study group for the Practical Deep Learning for Coders Part 2 course in late June. This study group will meet weekly on Saturdays at 8:45 am Pacific Time until October 5th. To join either of these groups, and to receive updates, visit https://twimlai.com/meetup or if you’ve already joined click “Update your profile” at the bottom of any TWIML email you’ve received. About the study groups The goal of the study groups are to provide support and encouragement to course participants to help them overcome any rough patches, stick with it longer, and learn more. We use the following to do this: FastAI channel on the TWIML slack. We’ll be collaborating via the TWIML Online Meetup Slack group, which you’ll automatically be invited to when you join the meetup. When study groups are underway the conversation there can be quite lively. Once you’ve joined the Slack, introduce yourself on the #intros channel and join the #fast_ai_dl channel. Weekly help sessions via Zoom. We meet weekly via video conference to discuss the week’s lesson, what we’ve learned so far, and any stumbling blocks. Participants are encouraged to join whether or not they have specific issues they need help with. How to Join To recap, here’s how to join: Sign up for the TWIML Online Meetup, checking the appropriate study groups in the programs section. Use the email invitation you’ll receive to join our Slack group. If you don’t receive it within a few minutes, check your spam folder. Once you’re in Slack, join the #fast_ai channel and hop over to #intros as well and introduce yourself. Cheers, Sam