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The third prize for the Best Project Competition in our course Computer Vision for Faces went to Andy Liang.
He is a C# developer who built a real-time face swapping mobile app based on the Unity framework for this final project.
The results are neat!
#ComputerVision, #MachineLearning, and #AI are the skills that are very applications-oriented.
You do not need the backing of a large company to build your own product.
If you want to learn how to build stunning applications using cutting-edge computer vision and machine learning algorithms, you must consider our course.
🌎 https://lnkd.in/gx_z6jf
❇️ @AI_Python
✴️ @AI_Python_EN
He is a C# developer who built a real-time face swapping mobile app based on the Unity framework for this final project.
The results are neat!
#ComputerVision, #MachineLearning, and #AI are the skills that are very applications-oriented.
You do not need the backing of a large company to build your own product.
If you want to learn how to build stunning applications using cutting-edge computer vision and machine learning algorithms, you must consider our course.
🌎 https://lnkd.in/gx_z6jf
❇️ @AI_Python
✴️ @AI_Python_EN
Maths behind a generative adversarial network (GAN) model and why it is hard to be trained. Wasserstein GAN is intended to improve GANs’ training
✅ http://bit.ly/2LFvIym #AI
#MachineLearning #DeepLearning #DataScience
❇️ @AI_Python
✴️ @AI_Python_EN
✅ http://bit.ly/2LFvIym #AI
#MachineLearning #DeepLearning #DataScience
❇️ @AI_Python
✴️ @AI_Python_EN
Deep Learning course: lecture slides and lab notebooks
https://m2dsupsdlclass.github.io/lectures-labs/
#منابع
❇️ @AI_Python
✴️ @AI_Python_EN
https://m2dsupsdlclass.github.io/lectures-labs/
#منابع
❇️ @AI_Python
✴️ @AI_Python_EN
The following is a list of free, open source books on machine learning, statistics, data-mining, etc.
#MachineLearning #DeepLearning #DataScience
🌎 Link Review
❇️ @AI_Python
✴️ @AI_Python_EN
#MachineLearning #DeepLearning #DataScience
🌎 Link Review
❇️ @AI_Python
✴️ @AI_Python_EN
This Google Tutorial (96 slides total) on Machine Learning is the best:
🌎 https://bit.ly/2kyUKne
#BigData #DataScience #NeuralNetworks #AI #DeepLearning #ML #Algorithms #DataScientists #ReinforcementLearning
❇️ @AI_Python
✴️ @AI_Python_EN
🌎 https://bit.ly/2kyUKne
#BigData #DataScience #NeuralNetworks #AI #DeepLearning #ML #Algorithms #DataScientists #ReinforcementLearning
❇️ @AI_Python
✴️ @AI_Python_EN
How Can You Build A Winning Machine Learning Algorithm?
http://bit.ly/2PV6tPv
#MachineLearning #ml #Algorithms
❇️ @AI_Python
✴️ @AI_Python_EN
http://bit.ly/2PV6tPv
#MachineLearning #ml #Algorithms
❇️ @AI_Python
✴️ @AI_Python_EN
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Introducing Amazon Go and the world’s most advanced shopping technology
Amazon Go is a new kind of store featuring the world's most advanced shopping technology. No lines, no checkout – just grab and go! Watch the video
#AI #ArtificialIntelligence
Is this the future Of shopping?
❇️ @AI_Python
✴️ @AI_Python_EN
Amazon Go is a new kind of store featuring the world's most advanced shopping technology. No lines, no checkout – just grab and go! Watch the video
#AI #ArtificialIntelligence
Is this the future Of shopping?
❇️ @AI_Python
✴️ @AI_Python_EN
"Condensing paragraphs into sentences isn’t easy for artificial intelligence (AI). That’s because it requires a semantic understanding of the text that’s beyond the capabilities of most off-the-shelf natural language processing models. But it’s not impossible, as researchers at Microsoft recently demonstrated.
In a paper published on the preprint server Arxiv.org (“Structured Neural Summarization“), scientists at Microsoft Research in Cambridge, England describe an AI framework that can reason about relationships in “weakly structured” text, enabling it to outperform conventional NLP models on a range of text summarization tasks."
https://venturebeat.com/2018/11/06/microsoft-researchers-develop-ai-system-that-can-generate-articles-summaries/
❇️ @AI_Python
✴️ @AI_Python_EN
In a paper published on the preprint server Arxiv.org (“Structured Neural Summarization“), scientists at Microsoft Research in Cambridge, England describe an AI framework that can reason about relationships in “weakly structured” text, enabling it to outperform conventional NLP models on a range of text summarization tasks."
https://venturebeat.com/2018/11/06/microsoft-researchers-develop-ai-system-that-can-generate-articles-summaries/
❇️ @AI_Python
✴️ @AI_Python_EN
"Training Neural Nets on Larger Batches: Practical Tips for 1-GPU, Multi-GPU & Distributed setups"
By Thomas Wolf: https://lnkd.in/etyMzjQ
#ArtificialInteligence #DeepLearning #MachineLearning #NeuralNetworks
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
By Thomas Wolf: https://lnkd.in/etyMzjQ
#ArtificialInteligence #DeepLearning #MachineLearning #NeuralNetworks
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Applying artificial intelligence for social good
🌎 http://bit.ly/2raCQLp
#AI #ArtificialIntelligence #MachineIntelligence #ML #MachineLearning #DataScience #Analytics
#BigData #IoT
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
🌎 http://bit.ly/2raCQLp
#AI #ArtificialIntelligence #MachineIntelligence #ML #MachineLearning #DataScience #Analytics
#BigData #IoT
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
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Playing first-person shooter games with webcam and #DeepLearning (Tensorflow #ObjectDetection)
Find out how you can use an object detection model to control and play any first-person shooter game with your computer's webcam. Links to the code below.
Full Video: https://lnkd.in/eBq7z4r
Blog: https://lnkd.in/eekrqWk
Code: https://lnkd.in/ekhwwiJ
Subscribe: youtube.com/c/DeepGamingAI
@AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Find out how you can use an object detection model to control and play any first-person shooter game with your computer's webcam. Links to the code below.
Full Video: https://lnkd.in/eBq7z4r
Blog: https://lnkd.in/eekrqWk
Code: https://lnkd.in/ekhwwiJ
Subscribe: youtube.com/c/DeepGamingAI
@AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
WOAH! OpenAI just released Spinning Up. A FREE resource for learning Deep Reinforcement Learning (RL).
Why Deep RL?
Because the beautiful thing about #DeepRL is much of the learning takes place by an agent in a virtual environment.
But wait... what's an agent? And what's an environment?
There's a new treatment available for patients with a certain issue. But she's hesitant to try it. She wants to wait for more trials to take place and more evidence to come out.
But running such trials in the real world is expensive and potentially harmful.
What if you could create a computer-generated version of Jessica (the agent), to try the treatment in a simulated medical centre (the environment) to see how it affected patients with similar characteristics to those in the real world?
With the knowledge you gain in the generated world, you could potentially improve the treatment and better suit it to each individual patient. Click HERE
❇️ @AI_Python
✴️ @AI_Python_EN
Why Deep RL?
Because the beautiful thing about #DeepRL is much of the learning takes place by an agent in a virtual environment.
But wait... what's an agent? And what's an environment?
There's a new treatment available for patients with a certain issue. But she's hesitant to try it. She wants to wait for more trials to take place and more evidence to come out.
But running such trials in the real world is expensive and potentially harmful.
What if you could create a computer-generated version of Jessica (the agent), to try the treatment in a simulated medical centre (the environment) to see how it affected patients with similar characteristics to those in the real world?
With the knowledge you gain in the generated world, you could potentially improve the treatment and better suit it to each individual patient. Click HERE
❇️ @AI_Python
✴️ @AI_Python_EN
CS231n: Convolutional Neural Networks for Visual Recognition ,This is the syllabus for the Spring 2018 iteration of the course.
Schedule and Syllabus university of stanford
http://cs231n.stanford.edu/syllabus.html
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Schedule and Syllabus university of stanford
http://cs231n.stanford.edu/syllabus.html
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Artificial Intelligence Projected Revenue
#artificialintelligence #ai
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
#artificialintelligence #ai
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Difference Between
#BusinessIntelligence and #DataScience
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
#BusinessIntelligence and #DataScience
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
🔥To our new subscribers 🔥
If you have trouble reading our posts in farsi which is 100% normal if you are not a native persian speaker 😃 i invite you to join english version of our channel:
✴️ @AI_Python_EN
PS: we have another channel called arXiv with a great AI bot that posts significant and recent articles submitted to arXiv on a daily basis:
🗣 @AI_Python_Arxiv
Thank you for joining our community of AI researchers and Python users.
Meysam Asgari on behalf of ai_python admins team.
❇️ @AI_Python
If you have trouble reading our posts in farsi which is 100% normal if you are not a native persian speaker 😃 i invite you to join english version of our channel:
✴️ @AI_Python_EN
PS: we have another channel called arXiv with a great AI bot that posts significant and recent articles submitted to arXiv on a daily basis:
🗣 @AI_Python_Arxiv
Thank you for joining our community of AI researchers and Python users.
Meysam Asgari on behalf of ai_python admins team.
❇️ @AI_Python
I think programming languages are called languages for a reason - and I think we all have a native and secondary language
Here's a handy lexicon between R and Python of sorts for your reference. It's sure to be handy, no matter which one is your native language!
🌎 https://lnkd.in/eG-Grrr
#datascience #dataanalysis #python #r
❇️ @AI_Python
🗣 @Data_Experts
✴️ @AI_Python_EN
Here's a handy lexicon between R and Python of sorts for your reference. It's sure to be handy, no matter which one is your native language!
🌎 https://lnkd.in/eG-Grrr
#datascience #dataanalysis #python #r
❇️ @AI_Python
🗣 @Data_Experts
✴️ @AI_Python_EN
All 10 talks from NeurIPS today:
https://lnkd.in/eYKW3Nv
#AI #ArtificialIntelligence #DeepLearning #MontrealArtificialIntelligence #NeurIPS #NeurIPS2018
❇️ @AI_Python
🗣 @Data_Experts
✴️ @AI_Python_EN
https://lnkd.in/eYKW3Nv
#AI #ArtificialIntelligence #DeepLearning #MontrealArtificialIntelligence #NeurIPS #NeurIPS2018
❇️ @AI_Python
🗣 @Data_Experts
✴️ @AI_Python_EN
How to build your own Neural Network from scratch in Python
🔵 A beginner’s guide to understanding the inner workings of Deep Learning
https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6
❇️ @AI_Python
🗣 @Data_Experts
✴️ @AI_Python_EN
🔵 A beginner’s guide to understanding the inner workings of Deep Learning
https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6
❇️ @AI_Python
🗣 @Data_Experts
✴️ @AI_Python_EN
Why learn Keras? This neutral network library is user-friendly and modular
🌎 https://jaxenter.com/keras-deep-learning-152388.html
✴️ @AI_Python_EN
🌎 https://jaxenter.com/keras-deep-learning-152388.html
✴️ @AI_Python_EN