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TemaDeep Learning

Lex FridmanPódcastFrom NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One LecturePresenta: Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.Modelos y entrenamientoReinforcement LearningDeep Learning+2

Lex FridmanPódcastTaming the Long Tail: How Waymo Builds a Self-Driving FactoryPresenta: Lex FridmanWaymo principal scientist Drago Anguelov explains how machine learning infrastructure, hybrid design and smart simulated agents tackle the rare events of autonomous driving.Modelos y entrenamientoAutonomous DrivingRobotics+3

Lex FridmanPódcastPolicy Gradients vs. Q-Learning: John Schulman's Field Guide to Deep Reinforcement LearningPresenta: Lex FridmanOpenAI's John Schulman walks through the core methods of deep RL, from the score function estimator to TRPO and DQN, and says when each one is worth using.Modelos y entrenamientoReinforcement LearningFundamentos de ML+3

Lex FridmanPódcastVapnik's Case for Learning by Predicates, Not Just by More DataPresenta: Lex FridmanIn an MIT lecture, Vladimir Vapnik argues that complete statistical learning needs two mechanisms, data and invariants, and that choosing smart predicates is where intelligence lives.Modelos y entrenamientoFundamentos de MLAI research+2

Lex FridmanPódcastTheano in an Hour: Symbolic Graphs, Automatic Gradients and a Compiler That Rewrites Your MathPresenta: Lex FridmanPascal Lamblin of MILA walks through how Theano builds, differentiates, optimizes and runs computation graphs, then trains logistic regression, a convnet and an LSTM.Modelos y entrenamientoDeep LearningFundamentos de ML+3

Lex FridmanPódcast · 2 vocesDeep Learning in One Lecture: From Perceptrons to AutoML and the Limits of LearningInvitado: Deep Learning Basics · Presenta: Lex FridmanLex Fridman's opening lecture for MIT's 6.S094 course surveys why deep learning took off, how neural networks learn, and where the technique still falls short.Modelos y entrenamientoDeep LearningFundamentos de ML+3

Lex FridmanPódcastDeep Reinforcement Learning, Explained by the Researcher Behind AlphaGoPresenta: Lex FridmanDavid Silver of DeepMind walks through what reinforcement learning is, how its building blocks fit together, and why deep neural networks keep surprising even the experts.Modelos y entrenamientoReinforcement LearningFundamentos de ML+3

Lex FridmanPódcastFrom Q-Tables to AlphaGo Zero: A Self-Driving Car Lecture on Deep Reinforcement LearningPresenta: Lex FridmanLex Fridman's MIT 6.S094 lecture walks from the AI pipeline and Q-learning to deep Q-networks, AlphaGo Zero and the DeepTraffic competition.Modelos y entrenamientoReinforcement LearningDeep Learning+3

Lex FridmanPódcastHands Off the Wheel in San Diego: A Comma Two Demo Drive and a Tour of comma.ai's Hardware ShopPresenta: Lex FridmanAfter their podcast conversation, George Hotz takes Lex Fridman on an openpilot drive and then through the comma.ai offices, dashboards, assembly line and compute cluster.Producto y UXAutonomous DrivingAI startups & small teams+3

Lex FridmanPódcastThe Second 90%: What It Really Takes to Put Deep Learning on a Driverless CarPresenta: Lex FridmanWaymo's Sacha Arnoud walks MIT students through Waymo's history, its perception stack, and the industrial-scale labeling, compute and testing behind it.Modelos y entrenamientoAutonomous DrivingRobotics+3

Lex FridmanPódcastInside Torch and Autograd: How Deep Learning Libraries Compute GradientsPresenta: Lex FridmanAlex Wiltschko of Twitter walks through Lua Torch, then explains automatic differentiation and what separates modern deep learning frameworks.Modelos y entrenamientoFundamentos de MLDeep Learning+1

Lex FridmanPódcast · 2 vocesIntelligence Is Not Just Prediction: David Ferrucci on Explanation, Persuasion and Shared MeaningInvitado: David Ferrucci · Presenta: Lex FridmanThe lead of IBM's Watson team argues that predicting well is only half of intelligence, and that being understood by others is the other half.PhilosophyAI researchAGI+2

Lex FridmanPódcastFrom Bag of Words to Attention: Quoc Le Teaches Sequence-to-Sequence Learning Through Email RepliesPresenta: Lex FridmanA Deep Learning School talk that builds sequence-to-sequence models step by step around one running example, automatic email reply, and then surveys memory and operation-augmented networks.Modelos y entrenamientoDeep LearningFundamentos de ML+2

Lex FridmanPódcastBigger Models, Cleaner Splits and Human Baselines: Andrew Ng's Practical Recipe for Applied Deep LearningPresenta: Lex FridmanIn a 2016 Deep Learning School talk, Andrew Ng distills lessons from leading Baidu's AI team into a workflow for diagnosing models, handling data and building a career.Modelos y entrenamientoFundamentos de MLDeep Learning+3

Lex FridmanPódcastLearning TensorFlow Hands-On: From a Mystery Line to Handwritten DigitsPresenta: Lex FridmanGoogle Brain's Sherry Moore walks a Deep Learning School audience through how TensorFlow works and two core labs, linear regression and MNIST digit recognition.Modelos y entrenamientoInfraestructura y despliegueOpen-source ecosystems+3

Lex FridmanPódcast · 2 vocesWhy Deep Learning Needs Rules: Chollet on Interpolation, Abstraction and Hybrid AIInvitado: François Chollet · Presenta: Lex FridmanFrançois Chollet explains why neural networks only interpolate between points they have seen, and why the best AI systems pair them with symbolic rules.Modelos y entrenamientoFundamentos de MLDeep Learning+2

Lex FridmanPódcastHow Machines Learn to See: From Pixel Differences to Convolutions, ResNets and Scene SegmentationPresenta: Lex FridmanLex Fridman's MIT 6.S094 lecture walks from the basics of image classification through landmark network architectures to pixel-level segmentation, optical flow and the SegFuse competition.Modelos y entrenamientoComputer VisionDeep Learning+3

Lex FridmanPódcastTeaching Cars to Watch the Driver: Deep Learning for Semi-Autonomous VehiclesPresenta: Lex FridmanLex Fridman's MIT 6.S094 lecture on using driver-facing cameras and neural networks to understand body pose, gaze, emotion and cognitive load.Modelos y entrenamientoAutonomous DrivingVisión y vídeo+3

Lex FridmanPódcast · 2 vocesRay Kurzweil on Hierarchies, the Neocortex and Merging with AIInvitado: Ray Kurzweil · Presenta: Lex FridmanIn an MIT AGI course lecture, Kurzweil connects the history of neural networks to his hierarchical theory of the neocortex, language understanding at Google, longevity, jobs and existential risk.Modelos y entrenamientoAGIAI History+3

Lex FridmanPódcast · 2 vocesCircuit Search, Hindsight and Self-Play: Ilya Sutskever's Case for Where Learning Is GoingInvitado: Ilya Sutskever · Presenta: Lex FridmanIn an MIT AGI lecture, OpenAI's co-founder explains why deep learning works, then walks through meta-learning, hindsight experience replay, sim-to-real transfer, self-play and learning goals from human feedback.Modelos y entrenamientoFundamentos de MLDeep Learning+3

Lex FridmanPódcastGlitches as Features: What John Hopfield Says Artificial Neural Networks Are MissingPresenta: Lex FridmanIn a short conversation with Lex Fridman, physicist and neural-network pioneer John Hopfield compares evolved brains with today's artificial networks and explains why he expects AI to borrow from biology generation after generation.Modelos y entrenamientoNeuroscience & AIFundamentos de ML+3

Lex FridmanPódcast · 2 vocesFrom a Side Project to TensorFlow's Core: François Chollet on How Keras Came to BeInvitado: François Chollet · Presenta: Lex FridmanThe creator of Keras recalls why he built it in 2015 around recurrent networks, how it moved onto TensorFlow, and what TensorFlow 2.0 means for its design.Código abierto y comunidadDeep LearningOpen-source ecosystems+3

Lex FridmanPódcast · 2 vocesStart Small, Build Habits, Pick Your Team: Andrew Ng's Practical Advice for Learning Deep LearningInvitado: Andrew Ng · Presenta: Lex FridmanIn a clip from the Lex Fridman Podcast, Andrew Ng explains how to begin in deep learning, how to study effectively, and how to choose a career path.Modelos y entrenamientoDeep LearningFundamentos de ML+3

Lex FridmanPódcastIs Driving More Like Chess or Conversation? Lex Fridman's Opening Lecture on Deep Learning for Self-Driving CarsPresenta: Lex FridmanThe first lecture of MIT 6.S094 introduces neural networks, reinforcement learning and computer vision through the question of how hard driving really is.Modelos y entrenamientoDeep LearningAutonomous Driving+3

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