The year in AI: 2019 #ML / #AI advances recap
It has become somewhat of a tradition for me to do an end-of-year retrospective of advances in AI/ML (see last year’s round up for example), so here we go again! This year started with a big recognition to the impact of #DeepLearning when #Hinton, #Bengio, and #Lecun were awarded the #Turing award.
Link
🔭 @DeepGravity
It has become somewhat of a tradition for me to do an end-of-year retrospective of advances in AI/ML (see last year’s round up for example), so here we go again! This year started with a big recognition to the impact of #DeepLearning when #Hinton, #Bengio, and #Lecun were awarded the #Turing award.
Link
🔭 @DeepGravity
Medium
The year in AI: 2019 ML/AI advances recap
It has become somewhat of a tradition for me to do an end-of-year retrospective of advances in AI/ML (see last year’s round up for…
Our reinforcement learning architect designs have been just published on #NeurIPS2019 AI Art Gallery:
https://lnkd.in/dFZ37BN
Seems it draws like a baby now, but is growing and hopefully would be a skillful #RL artist very soon.
#reinforcementlearning #deeplearning #ai #artificialintelligence #art #deepreinforcementlearning #creativeart #neurips
🔭 @DeepGravity
https://lnkd.in/dFZ37BN
Seems it draws like a baby now, but is growing and hopefully would be a skillful #RL artist very soon.
#reinforcementlearning #deeplearning #ai #artificialintelligence #art #deepreinforcementlearning #creativeart #neurips
🔭 @DeepGravity
AI Art Gallery
Yuta Akizuki, Mathias Bernhard, Reza Kakooee, Marirena Kladeftira, Benjamin Dillenburger - AI Art Gallery
Generative Modelling with Design Constraints – Reinforcement Learning for Furniture Generation (2019) Generative design has been…
Seven differences between academia and industry for building machine learning and #deepLearning models
1) Approach to accuracy
2) Training vs serving
3) Emphasis on Engineering
4) Less emphasis on larger models
5) Understanding the baseline
6) Understanding the intricacies of data
7) Focusing on deep learning too early
Link
🔭 @DeepGravity
1) Approach to accuracy
2) Training vs serving
3) Emphasis on Engineering
4) Less emphasis on larger models
5) Understanding the baseline
6) Understanding the intricacies of data
7) Focusing on deep learning too early
Link
🔭 @DeepGravity
Datasciencecentral
Seven differences between academia and industry for building machine learning and deep learning models
Academia and industry take different approaches to building machine learning and deep learning models
Here are seven differences
1) Approach to accura…
#TensorFlow 2 Tutorial: Get Started in #DeepLearning With tf.keras
After completing this tutorial, you will know:
The difference between Keras and tf.keras and how to install and confirm TensorFlow is working.
The 5-step life-cycle of tf.keras models and how to use the sequential and functional APIs.
How to develop MLP, CNN, and RNN models with tf.keras for regression, classification, and time series forecasting.
How to use the advanced features of the tf.keras API to inspect and diagnose your model.
How to improve the performance of your tf.keras model by reducing overfitting and accelerating training.
#Keras
Link
🔭 @DeepGravity
After completing this tutorial, you will know:
The difference between Keras and tf.keras and how to install and confirm TensorFlow is working.
The 5-step life-cycle of tf.keras models and how to use the sequential and functional APIs.
How to develop MLP, CNN, and RNN models with tf.keras for regression, classification, and time series forecasting.
How to use the advanced features of the tf.keras API to inspect and diagnose your model.
How to improve the performance of your tf.keras model by reducing overfitting and accelerating training.
#Keras
Link
🔭 @DeepGravity
During the last two days, some famous #MachineLearning researchers elucidated their own definition of #DeepLearning. You might check the related links to read full definitions and discussions on each.
Yann LeCun:
#DL is constructing networks of parameterized functional modules & training them from examples using gradient-based optimization. That's it.
This definition is orthogonal to the learning paradigm: reinforcement, supervised, or self-supervised.
https://www.facebook.com/722677142/posts/10156463919392143/
Andriy Burkov:
Looks like in late 2019, people still need a definition of deep learning, so here's mine: deep learning is finding parameters of a nested parametrized non-linear function by minimizing an example-based differentiable cost function using gradient descent.
https://www.linkedin.com/posts/andriyburkov_looks-like-in-late-2019-people-still-need-activity-6615377527147941888-ce68/
François Chollet:
Deep learning refers to an approach to representation learning where your model is a chain of modules (typically a stack / pyramid, hence the notion of depth), each of which could serve as a standalone feature extractor if trained as such.
https://twitter.com/fchollet/status/1210031900695449600
Link
🔭 @DeepGravity
Yann LeCun:
#DL is constructing networks of parameterized functional modules & training them from examples using gradient-based optimization. That's it.
This definition is orthogonal to the learning paradigm: reinforcement, supervised, or self-supervised.
https://www.facebook.com/722677142/posts/10156463919392143/
Andriy Burkov:
Looks like in late 2019, people still need a definition of deep learning, so here's mine: deep learning is finding parameters of a nested parametrized non-linear function by minimizing an example-based differentiable cost function using gradient descent.
https://www.linkedin.com/posts/andriyburkov_looks-like-in-late-2019-people-still-need-activity-6615377527147941888-ce68/
François Chollet:
Deep learning refers to an approach to representation learning where your model is a chain of modules (typically a stack / pyramid, hence the notion of depth), each of which could serve as a standalone feature extractor if trained as such.
https://twitter.com/fchollet/status/1210031900695449600
Link
🔭 @DeepGravity
Dive into Deep Learning
An interactive #DeepLearning #book with code, math, and discussions, based on the #NumPy interface.
Book
🔭 @DeepGravity
An interactive #DeepLearning #book with code, math, and discussions, based on the #NumPy interface.
Book
🔭 @DeepGravity
درود بر همهی شما دوستان گرامی،
امیدوارم این روزهای سخت بهاری به زودی با چیرگی سبزی بر سیاهی سپری بشه. هر چند اندوهش هرگز از یادها نخواهد رفت.
به منظور بررسی ابعاد بحران #کرونا از نگاه #ماشین_لرنینگ، قصد دارم به کمک شما عزیزان یک جلسهی هماندیشی آنلاین رو راهاندازی کنم. در لینک زیر زمانهای مختلفی رو میبینین. لطفا زمانی که برای شما مناسبتره رو انتخاب کنین که تو اون تایم از طریق زوم یا گوگل میت بتونیم دور هم جمع بشیم. سعی کردم گزینهها رو بین صبح و عصر و شب پخش کنم که با توجه به اختلاف ساعتها بتونیم تایم مشترکی رو پیدا کنیم:
https://doodle.com/poll/69fvgkegwq3y8p6w
هدف این جلسه بیشتر هم اندیشی و به اشتراک گذاری دانستهها و داشتهها ست. من خودم دو تا رپو آماده کردم که در موردشون توضیح خواهم داد.
(هدف مقاله دادن یا کار اقتصادی کردن نیست)
امیدوارم ما هم بتونیم در کنار تیم درمان، کمکی برای کشور (و شاید دنیا) در این شرایط باشیم.
اگه پیشنهادی هم دارین، لطفا در کامنت یا به صورت خصوصی پیام بذارین.
ارادتمند
#ai #computervision #machinelearning #deeplearning #covid19
@Reza
🔭 @DeepGravity
امیدوارم این روزهای سخت بهاری به زودی با چیرگی سبزی بر سیاهی سپری بشه. هر چند اندوهش هرگز از یادها نخواهد رفت.
به منظور بررسی ابعاد بحران #کرونا از نگاه #ماشین_لرنینگ، قصد دارم به کمک شما عزیزان یک جلسهی هماندیشی آنلاین رو راهاندازی کنم. در لینک زیر زمانهای مختلفی رو میبینین. لطفا زمانی که برای شما مناسبتره رو انتخاب کنین که تو اون تایم از طریق زوم یا گوگل میت بتونیم دور هم جمع بشیم. سعی کردم گزینهها رو بین صبح و عصر و شب پخش کنم که با توجه به اختلاف ساعتها بتونیم تایم مشترکی رو پیدا کنیم:
https://doodle.com/poll/69fvgkegwq3y8p6w
هدف این جلسه بیشتر هم اندیشی و به اشتراک گذاری دانستهها و داشتهها ست. من خودم دو تا رپو آماده کردم که در موردشون توضیح خواهم داد.
(هدف مقاله دادن یا کار اقتصادی کردن نیست)
امیدوارم ما هم بتونیم در کنار تیم درمان، کمکی برای کشور (و شاید دنیا) در این شرایط باشیم.
اگه پیشنهادی هم دارین، لطفا در کامنت یا به صورت خصوصی پیام بذارین.
ارادتمند
#ai #computervision #machinelearning #deeplearning #covid19
@Reza
🔭 @DeepGravity
Doodle
Doodle: The COVID-19 Aspects
For Iranians in AI