Super Data Science: ML & AI Podcast with Jon Krohn
999 episodes — Page 7 of 20
698: How Firms Can Actually Adopt A.I., with Rehgan Avon
Jul 21, 202327 min
697: The (Short) Path to Artificial General Intelligence, with Dr. Ben Goertzel
Jul 18, 20231h 27m
696: Brain-Computer Interfaces and Neural Decoding, with Prof. Bob Knight
Jul 14, 20231h 2m
695: NLP with Transformers, feat. Hugging Face's Lewis Tunstall
Jul 11, 20231h 38m
694: CatBoost: Powerful, efficient ML for large tabular datasets
Jul 7, 20237 min
693: YOLO-NAS: The State of the Art in Machine Vision, with Harpreet Sahota
Jul 4, 20231h 20m
692: Lossless LLM Weight Compression: Run Huge Models on a Single GPU
Jun 30, 20237 min
691: A.I. Accelerators: Hardware Specialized for Deep Learning
Jun 27, 20231h 34m
690: How to Catch and Fix Harmful Generative A.I. Outputs
Jun 23, 202326 min
689: Observing LLMs in Production to Automatically Catch Issues
Jun 20, 20231h 18m
688: Six Reasons Why Building LLM Products Is Tricky
Jun 16, 202314 min
687: Generative Deep Learning, with David Foster
Jun 13, 20231h 46m
686: Open-Source "Responsible A.I." Tools, with Ruth Yakubu
Jun 9, 202329 min
685: Tools for Building Real-Time Machine Learning Applications, with Richmond Alake
Jun 6, 20231h 6m
684: Get More Language Context out of your LLM
Jun 2, 20235 min
683: Contextual A.I. for Adapting to Adversaries, with Dr. Matar Haller
May 30, 20231h 20m
682: Business Intelligence Tools, with Mico Yuk
May 26, 202327 min
681: XGBoost: The Ultimate Classifier, with Matt Harrison
May 23, 20231h 12m
680: Automating Industrial Machines with Data Science and the Internet of Things (IoT)
May 19, 202330 min
679: The A.I. and Machine Learning Landscape, with investor George Mathew
May 16, 20231h 34m
678: StableLM: Open-source "ChatGPT"-like LLMs you can fit on one GPU
May 12, 202311 min
677: Digital Analytics with Avinash Kaushik
May 9, 20231h 27m
676: The Chinchilla Scaling Laws
May 5, 202313 min
675: Pandas for Data Analysis and Visualization
May 2, 20231h 8m
674: Parameter-Efficient Fine-Tuning of LLMs using LoRA (Low-Rank Adaptation)
Apr 28, 20235 min
673: Taipy, the open-source Python application builder
Apr 25, 20231h 12m
672: Open-source "ChatGPT": Alpaca, Vicuña, GPT4All-J, and Dolly 2.0
Apr 21, 202316 min
671: Cloud Machine Learning
Apr 18, 20231h 3m
670: LLaMA: GPT-3 performance, 10x smaller
Apr 14, 202313 min
669: Streaming, reactive, real-time machine learning
Apr 11, 20231h 40m
668: GPT-4: Apocalyptic stepping stone?
Apr 7, 202355 min
667: Harnessing GPT-4 for your Commercial Advantage
Apr 4, 20231h 4m
666: GPT-4
Mar 31, 202311 min
665: How to be both socially impactful and financially successful in your data career
Mar 28, 20231h 27m
664: MIT Study: ChatGPT Dramatically Increases Productivity
Mar 24, 20235 min
663: Astonishing CICERO negotiates and builds trust with humans using natural language
Mar 21, 20231h 17m
662: The Most Popular SuperDataScience Podcast Episodes of 2022
Mar 17, 20237 min
661: Designing Machine Learning Systems
Mar 14, 20231h 16m
660: Five Ways to Use ChatGPT for Data Science
Mar 10, 20233 min
659: Open-Source Tools for Natural Language Processing
Mar 7, 20231h 20m
658: How to Build Data and ML Products Users Love
Mar 3, 202335 min
657: How to Learn Data Engineering
Feb 28, 20231h 9m
656: A.I. Talent and the Red-Hot A.I. Skills
Feb 24, 202341 min
655: AI ROI: How to get a profitable return on an AI-project investment
Feb 21, 20231h 43m
654: Mike Wimmer: The 14-Year-Old A.I. Entrepreneur
Feb 17, 202345 min
653: Efficiently Glean-ing Insights from Vast Data Warehouses
Feb 14, 202357 min
652: A.I. Speech for the Speechless
Feb 10, 20236 min
651: The Intentional Use of Color in Data Communication
Feb 7, 20231h 16m
650: SparseGPT: Remove 100 Billion Parameters but Retain 100% Accuracy
Feb 3, 20237 min
649: Introduction to Machine Learning
Jan 31, 20231h 22m