Artificial Intelligence && Deep Learning

MIT Introduction to Deep Learning - 2023 Starting soon! MIT Intro to DL is one of the most concise AI courses on the web that cover basic deep learning techniques, architectures, and applications.

2023 lectures are starting in just one day, Jan 9th!

Link to register:
http://introtodeeplearning.com

MIT Introduction to Deep Learning The 2022 lectures can be found here:

https://m.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI

invite your friends 🌹🌹🌹
@Deeplearning_ai

29.8K viewsSHOHRUH, edited 23:17

Welcome to the Ultralytics YOLOv8 🚀 notebook! YOLOv8 is the latest version of the YOLO object detection and image segmentation model developed by Ultralytics.
The YOLOv8 models are designed to be fast, accurate, and easy to use, making them an excellent choice for a wide range of object detection and image segmentation tasks.

source code: https://github.com/ultralytics/ultralytics

colab : https://colab.research.google.com/github/ultralytics/ultralytics/blob/main/examples/tutorial.ipynb#scrollTo=t6MPjfT5NrKQ

MIT Introduction to Deep Learning - 2023 Starting soon! MIT Intro to DL is one of the most concise AI courses on the web that cover basic deep learning techniques, architectures, and applications.

Link to register:
http://introtodeeplearning.com

MIT Introduction to Deep Learning The 2022 lectures can be found here:

https://m.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI

@Deeplearning_ai

29.7K viewsSHOHRUH, edited 04:54

1:01

YOLOv8 is the newest state-of-the-art YOLO model that can be used for object detection, image classification, and instance segmentation tasks. YOLOv8 includes numerous architectural and developer experience changes and improvements over YOLOv5.

Code:
https://github.com/ultralytics/ultralytics

What's New in YOLOv8 ?
https://blog.roboflow.com/whats-new-in-yolov8/

Yolov8 Instance Segmentation (ONNX):
https://github.com/ibaiGorordo/ONNX-YOLOv8-Instance-Segmentation

@Deeplearning_ai

30.1K viewsSHOHRUH, edited 02:30

Access to high-paying remote web3 jobs: https://t.me/web3hiring

Web3 networking & discussion group: https://t.me/hashtagweb3

32.3K viewsSHOHRUH, 03:12

animation.gif

12.2 MB

Accurate and Efficient Stereo Matching via Attention Concatenation Volume

Stereo Depth Estimation

Paper:
https://arxiv.org/pdf/2209.12699.pdf

Github:
https://github.com/gangweiX/Fast-ACVNet

Demo:
https://www.youtube.com/watch?v=az4Z3dp72Zw

@Deeplearning_ai

36.5K viewsSHOHRUH, edited 07:52

VTOONIFY: CONTROLLABLE HIGH-RESOLUTION PORTRAIT VIDEO STYLE TRANSFER

Project page: https://www.mmlab-ntu.com/project/vtoonify/

G.COLAB: https://colab.research.google.com/github/williamyang1991/VToonify/blob/master/notebooks/inference_playground.ipynb

source code: https://github.com/williamyang1991/vtoonify

Paper: VToonify: Controllable High-Resolution Portrait Video Style Transfer

@Deeplearning_ai

37.6K viewsSHOHRUH, edited 02:56

DiffusionInst: Diffusion Model for Instance Segmentation

* DiffusionInst is the first work of diffusion model for instance segmentation

Github:
https://github.com/chenhaoxing/DiffusionInst

Paper:
https://arxiv.org/abs/2212.02773v2

Getting started:
https://github.com/chenhaoxing/DiffusionInst/blob/main/GETTING_STARTED.md

Dataset:
https://paperswithcode.com/dataset/lvis

@DeepLearning_ai

36.0K views..., edited 00:40

https://youtu.be/yIFCQGBrHls

YouTube

What is Machine Learning? | Basics of Machine Learning | Introduction to Machine learning

Are you fascinated by the power of technology and the endless possibilities it presents? Look no further than Machine Learning, the cutting-edge branch of Artificial Intelligence that's taking the world by storm.

In this video, we'll explore the amazing…

36.9K views..., 10:36

0:15

Machine Learning Operations (MLOps) Masterclass

🏆 Unlock your full potential with MLOps Masterclass

Learn to Design ML Pipelines to Build, Train,Deploy and Monitor your Machine learning models in a real-time production environment.

Register Now👇

https://bit.ly/mlops-class

Why you shouldn't miss this Masterclass?
✔️ 15+ hands-on exercises.
✔️ 2 Real-life industry projects.
✔️Dedicated mentoring sessions from industry experts.
✔️ 10 hours session consisting of theory + Hands-on.

Schedule:
11th,Sat & 12th,Sun March

Highlights of this Masterclass:
▪️Machine Learning Operations (MLOps) Introduction
▪️Getting started with AWS for Machine Learning
▪️AWS SageMaker
▪️CI/CD Tools
▪️AWS MLOps Tools
▪️AWS MLOps - Build, Train & deploy ML Model

38.7K viewsShohruh, 02:41

0:31

3D-aware Conditional Image Synthesis (pix2pix3D)

Pix2pix3D synthesizes 3D objects (neural fields) given a 2D label map, such as a segmentation or edge map

Github:
https://github.com/dunbar12138/pix2pix3D

Paper:
https://arxiv.org/abs/2302.08509

Project:
https://www.cs.cmu.edu/~pix2pix3D/

Datasets:
CelebAMask , AFHQ-Cat-Seg , Shapenet-Car-Edge

@deeplearning_ai

40.7K viewsShohruh, 02:03

GPT-4 Technical Report

Source code: https://github.com/openai/evals

Paper: https://cdn.openai.com/papers/gpt-4.pdf

@deeplearning_ai

32.7K viewsShohruh, edited 05:21

🔥 Machine Learning Operations (MLOps) Specialization Course Demo

# FREE CLASS

Learn to Design production-ready ML Pipelines to Build, Train and Deploy your Machine learning models on AWS, Azure, GCP & Open- Source tools

📈 Key Highlights of course
✔️ 40 Hours of Live sessions from Industrial Experts
✔️ 50+ Live Hands-on Labs
✔️ 5+ Real-time industrial projects
✔️ One-on-One with Industry Mentors

👉🏻 Registration Link
https://bit.ly/mlops-live

🧑🏻‍🎓 What You Will Learn?
▪️Introduction to ML and MLOps stages
▪️Introduction to Git & CI/CD
▪️Docker & Kubernetes Overview
▪️Kubernetes Deployment Strategy
▪️Introduction to Model Management
▪️Feature Store
▪️Cloud ML Services 101
▪️Kubeflow Intro
▪️Introduction to Model Monitoring
▪️Introduction to Automl tools
▪️Post-Deployment Challenges

☎️ Contact:
Sarath Kumar
+918940876397 / +918778033930

38.9K viewsShohruh, 06:00

36.0K viewsShohruh, 23:07

"A panda is playing guitar on times square"

Text2Video-Zero

Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators

Paper: https://arxiv.org/abs/2303.13439
Video Result: video result link
Source code: https://github.com/picsart-ai-research/text2video-zero

Join us: @deeplarning_ai

42.7K viewsShohruh, 00:41

"A panda is playing guitar on times square" Text2Video-Zero Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators Paper: https://arxiv.org/abs/2303.13439 Video Result: video result link Source code: https://github.com/picsart-ai…

reallyyyy amazing......

43.4K viewsShohruh, edited 00:44

Big News! Meta just released Segment Anything, a new AI model that can "cut out" any object, in any image/video, with a single click.

The model is designed and trained to be promptable, so it can transfer zero-shot to new image distributions and tasks.

https://segment-anything.com/

Check out https://AlphaSignal.ai to get a weekly summary of the top breakthroughs in Machine Learning.

@deeplearning_ai

43.6K viewsShohruh, 01:34

CS 330 Deep Multi-Task and Meta Learning

Stanford CS330: Deep Multi-Task and Meta Learning.

While deep learning has achieved remarkable success in many problems such as image classification, natural language processing, and speech recognition, these models are, to a large degree, specialized for the single task they are trained for. This course will cover the setting where there are multiple tasks to be solved, and study how the structure arising from multiple tasks can be leveraged to learn more efficiently or effectively. This includes:

- self-supervised pre-training for downstream few-shot learning and transfer learning
meta-learning methods that aim to learn efficient learning algorithms that can learn new tasks quickly
- curriculum and lifelong learning, where the problem requires learning a sequence of tasks, leveraging their shared structure to enable knowledge transfer

Course Schedule and Materials:
https://cs330.stanford.edu/

GET Free Course Link

Join us: @deeplarning_ai

cs330.stanford.edu

39.4K views..., edited 08:30