Building Generative AI Applications with Gradio Now Available!

DeepLearningAI · Intermediate ·🧠 Large Language Models ·2y ago

Key Takeaways

Builds interactive generative AI applications with Gradio and Hugging Face Spaces

Full Transcript

I'm excited to share with you this new course on building generative AI applications using radio this is built in collaboration with our polynarial puzzles who goes by poly and many of his colleagues at hugging face thanks Andrew happy to be here large language models LMS such as chat GPT have taken the World by storm for developers they provide a way to build applications quickly maybe in minutes or hours but when you build something by say prompting an OM to carry out see a text processing tasks like summarization or building a chatbot if you've built an image generation model using a diffusion model how can you demo what you build to others either to get feedback or because you just want others to experience what you built this course will show you how to accomplish that quickly just by writing python codes using radio we will build interactive applications with generative Ai and the chatbot that you'll build will allow you to chat with the top ranked open source llm called Falcon I hope you enjoy the course and that after finishing it that you use what you learn to build some really cool demos to show others [Music] foreign

Original Description

Enroll today: https://bit.ly/3XXAApp Join our new short course developed in collaboration with Hugging Face, Building Generative AI Applications with Gradio! Learn how to leverage Gradio, a Hugging Face product built to help you to transform your inference code into easy-to-use demos ready for trial on Hugging Face Spaces. You’ll gain the practical knowledge to rapidly build interactive apps and demos to validate your project and ship faster. Our course covers: How to create a user-friendly app (usable for non-coders) with a few lines of code to take input text, summarize it with an open-source large language model, and display the summary. How to build an app that allows the user to upload an image, which uses image-to-text (image captioning) to describe the uploaded image, and display both the image and the caption in the app. How to create an interface to chat with an open-source LLM using Falcon, the best-ranking open-source LLM on the Open LLM Leaderboard. And more! Sign up today and start learning from Apolinário Passos, Machine Learning Art Engineer at Hugging Face! Learn more: https://bit.ly/3XXAApp
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Playlist

Uploads from DeepLearningAI · DeepLearningAI · 0 of 60

← Previous Next →
1 Forward and Backward Propagation (C1W4L06)
Forward and Backward Propagation (C1W4L06)
DeepLearningAI
 2 deeplearning.ai's Heroes of Deep Learning: Yuanqing Lin
deeplearning.ai's Heroes of Deep Learning: Yuanqing Lin
DeepLearningAI
 3 deeplearning.ai's Heroes of Deep Learning: Ruslan Salakhutdinov
deeplearning.ai's Heroes of Deep Learning: Ruslan Salakhutdinov
DeepLearningAI
 4 deeplearning.ai's Heroes of Deep Learning: Yoshua Bengio
deeplearning.ai's Heroes of Deep Learning: Yoshua Bengio
DeepLearningAI
 5 deeplearning.ai's Heroes of Deep Learning: Pieter Abbeel
deeplearning.ai's Heroes of Deep Learning: Pieter Abbeel
DeepLearningAI
 6 deeplearning.ai's Heroes of Deep Learning: Ian Goodfellow
deeplearning.ai's Heroes of Deep Learning: Ian Goodfellow
DeepLearningAI
 7 deeplearning.ai's Heroes of Deep Learning: Andrej Karpathy
deeplearning.ai's Heroes of Deep Learning: Andrej Karpathy
DeepLearningAI
 8 Using an Appropriate Scale (C2W3L02)
Using an Appropriate Scale (C2W3L02)
DeepLearningAI
 9 Gradient Checking (C2W1L13)
Gradient Checking (C2W1L13)
DeepLearningAI
 10 Gradient Checking Implementation Notes (C2W1L14)
Gradient Checking Implementation Notes (C2W1L14)
DeepLearningAI
 11 Learning Rate Decay (C2W2L09)
Learning Rate Decay (C2W2L09)
DeepLearningAI
 12 Understanding Mini-Batch Gradient Dexcent (C2W2L02)
Understanding Mini-Batch Gradient Dexcent (C2W2L02)
DeepLearningAI
 13 Mini Batch Gradient Descent (C2W2L01)
Mini Batch Gradient Descent (C2W2L01)
DeepLearningAI
 14 The Problem of Local Optima (C2W3L10)
The Problem of Local Optima (C2W3L10)
DeepLearningAI
 15 Exponentially Weighted Averages (C2W2L03)
Exponentially Weighted Averages (C2W2L03)
DeepLearningAI
 16 Tuning Process (C2W3L01)
Tuning Process (C2W3L01)
DeepLearningAI
 17 Understanding Exponentially Weighted Averages (C2W2L04)
Understanding Exponentially Weighted Averages (C2W2L04)
DeepLearningAI
 18 Bias Correction of Exponentially Weighted Averages (C2W2L05)
Bias Correction of Exponentially Weighted Averages (C2W2L05)
DeepLearningAI
 19 Gradient Descent With Momentum (C2W2L06)
Gradient Descent With Momentum (C2W2L06)
DeepLearningAI
 20 Normalizing Activations in a Network (C2W3L04)
Normalizing Activations in a Network (C2W3L04)
DeepLearningAI
 21 Hyperparameter Tuning in Practice (C2W3L03)
Hyperparameter Tuning in Practice (C2W3L03)
DeepLearningAI
 22 Adam Optimization Algorithm (C2W2L08)
Adam Optimization Algorithm (C2W2L08)
DeepLearningAI
 23 RMSProp (C2W2L07)
RMSProp (C2W2L07)
DeepLearningAI
 24 Fitting Batch Norm Into Neural Networks (C2W3L05)
Fitting Batch Norm Into Neural Networks (C2W3L05)
DeepLearningAI
 25 Why Does Batch Norm Work? (C2W3L06)
Why Does Batch Norm Work? (C2W3L06)
DeepLearningAI
 26 Batch Norm At Test Time (C2W3L07)
Batch Norm At Test Time (C2W3L07)
DeepLearningAI
 27 Softmax Regression (C2W3L08)
Softmax Regression (C2W3L08)
DeepLearningAI
 28 Deep Learning Frameworks (C2W3L10)
Deep Learning Frameworks (C2W3L10)
DeepLearningAI
 29 Neural Network Overview (C1W3L01)
Neural Network Overview (C1W3L01)
DeepLearningAI
 30 Training Softmax Classifier (C2W3L09)
Training Softmax Classifier (C2W3L09)
DeepLearningAI
 31 Why Deep Representations? (C1W4L04)
Why Deep Representations? (C1W4L04)
DeepLearningAI
 32 Gradient Descent For Neural Networks (C1W3L09)
Gradient Descent For Neural Networks (C1W3L09)
DeepLearningAI
 33 Neural Network Representations (C1W3L02)
Neural Network Representations (C1W3L02)
DeepLearningAI
 34 TensorFlow (C2W3L11)
TensorFlow (C2W3L11)
DeepLearningAI
 35 Activation Functions (C1W3L06)
Activation Functions (C1W3L06)
DeepLearningAI
 36 Explanation For Vectorized Implementation (C1W3L05)
Explanation For Vectorized Implementation (C1W3L05)
DeepLearningAI
 37 Getting Matrix Dimensions Right (C1W4L03)
Getting Matrix Dimensions Right (C1W4L03)
DeepLearningAI
 38 Understanding Dropout (C2W1L07)
Understanding Dropout (C2W1L07)
DeepLearningAI
 39 Building Blocks of a Deep Neural Network (C1W4L05)
Building Blocks of a Deep Neural Network (C1W4L05)
DeepLearningAI
 40 Why Non-linear Activation Functions (C1W3L07)
Why Non-linear Activation Functions (C1W3L07)
DeepLearningAI
 41 Computing Neural Network Output (C1W3L03)
Computing Neural Network Output (C1W3L03)
DeepLearningAI
 42 Backpropagation Intuition (C1W3L10)
Backpropagation Intuition (C1W3L10)
DeepLearningAI
 43 Train/Dev/Test Sets (C2W1L01)
Train/Dev/Test Sets (C2W1L01)
DeepLearningAI
 44 Deep L-Layer Neural Network (C1W4L01)
Deep L-Layer Neural Network (C1W4L01)
DeepLearningAI
 45 Random Initialization (C1W3L11)
Random Initialization (C1W3L11)
DeepLearningAI
 46 Other Regularization Methods (C2W1L08)
Other Regularization Methods (C2W1L08)
DeepLearningAI
 47 Normalizing Inputs (C2W1L09)
Normalizing Inputs (C2W1L09)
DeepLearningAI
 48 Derivatives Of Activation Functions (C1W3L08)
Derivatives Of Activation Functions (C1W3L08)
DeepLearningAI
 49 Parameters vs Hyperparameters (C1W4L07)
Parameters vs Hyperparameters (C1W4L07)
DeepLearningAI
 50 Vectorizing Across Multiple Examples (C1W3L04)
Vectorizing Across Multiple Examples (C1W3L04)
DeepLearningAI
 51 What does this have to do with the brain? (C1W4L08)
What does this have to do with the brain? (C1W4L08)
DeepLearningAI
 52 Dropout Regularization (C2W1L06)
Dropout Regularization (C2W1L06)
DeepLearningAI
 53 Vanishing/Exploding Gradients (C2W1L10)
Vanishing/Exploding Gradients (C2W1L10)
DeepLearningAI
 54 Basic Recipe for Machine Learning (C2W1L03)
Basic Recipe for Machine Learning (C2W1L03)
DeepLearningAI
 55 Bias/Variance (C2W1L02)
Bias/Variance (C2W1L02)
DeepLearningAI
 56 Forward Propagation in a Deep Network (C1W4L02)
Forward Propagation in a Deep Network (C1W4L02)
DeepLearningAI
 57 Weight Initialization in a Deep Network (C2W1L11)
Weight Initialization in a Deep Network (C2W1L11)
DeepLearningAI
 58 Numerical Approximations of Gradients (C2W1L12)
Numerical Approximations of Gradients (C2W1L12)
DeepLearningAI
 59 Regularization (C2W1L04)
Regularization (C2W1L04)
DeepLearningAI
 60 Why Regularization Reduces Overfitting (C2W1L05)
Why Regularization Reduces Overfitting (C2W1L05)
DeepLearningAI

Related Reads

Up next
5 Levels of AI Agents - From Simple LLM Calls to Multi-Agent Systems
Dave Ebbelaar (LLM Eng)
Watch →