آموزش های هوش مصنوعی دکتر اله یاری

Seq2seq Learning Example Part 1

#منابع #فیلم #دانشگاه #الگوریتمها #کلاس_آموزشی #یادگیری_ماشین #هوش_مصنوعی
#machinelearning #ArtificialIntelligence #DeepLearning

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🗣 @AI_Python_arXiv
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آموزش های هوش مصنوعی دکتر اله یاری

Seq2seq Learning Example Part 2

#منابع #فیلم #دانشگاه #الگوریتمها #کلاس_آموزشی #یادگیری_ماشین #هوش_مصنوعی
#machinelearning #ArtificialIntelligence #DeepLearning

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🗣 @AI_Python_arXiv
✴️ @AI_Python_EN

آموزش های هوش مصنوعی دکتر اله یاری

RNN and LSTM Networks Tutorial Part 1

#منابع #فیلم #دانشگاه #الگوریتمها #کلاس_آموزشی #یادگیری_ماشین #هوش_مصنوعی
#machinelearning #ArtificialIntelligence #DeepLearning

❇️ @AI_Python
🗣 @AI_Python_arXiv
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همه چی در مورد انباره داده ها Data Warehouse

#الگوریتمها #هوش_مصنوعی #علم_داده #منابع
#DataScience #ArtificialIntelligence #AI

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✴️ @AI_Python_en

Lecture Notes in Deep Learning: Feedforward Networks — Part 3 | #DataScience #MachineLearning #ArtificialIntelligence #AI

https://bit.ly/2Z2GgQY

Reinforcement Learning

Let's say we have an agent in an unknown environment and this agent can obtain some rewards by interacting with the environment.

The agent is tasked to take actions so as to maximize cumulative rewards. In reality, the scenario could be a bot playing a game to achieve high scores, or a robot trying to complete physical tasks with physical items; and not just limited to these.

Like humans, RL agents learn for themselves to achieve successful strategies that lead to the greatest long-term rewards.

This kind of learning by trial-and-error, based on rewards or punishments, is known as reinforcement learning (RL).

TensorTrade is an open-source Python framework for building, training, evaluating, and deploying robust trading algorithms using reinforcement learning.

https://github.com/tensortrade-org/tensortrade

#artificialintelligence #machinelearning #datascience #datascience #python

🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
❇️ @AI_Python

AI is a Lie

Imagine this to be true for a moment Imagine

there’s a group of few weird animals who are pretending to be ‘AI’

These animals have one special power

Whenever you ask them a question they would reply back with a decision

But your question should be supported with some examples for them to learn from

For example:

- If I ask the animals to determine whether a person is happy or sad

The animals would need to be first trained through some examples in order to understand the 2 types of emotions

Sadly their decisions won’t be perfect always

But if you keep training them with more examples they are likely to improve their decision making abilities

Also there are various types of these animals some who require less examples while some who require more It’s your call to choose which animal should answer your question You can even choose mutliple animals This is how ML works in real-life too ML models (Animals) learn through examples and takes decisions based on the input given It’s your call to choose which model The output won’t be perfect always But if you keep on training your model with relevant new examples It’d learn to improvise What would you want these animals to do for you? #machinelearning #datascience #artificialintelligence

By explaining a model's decisions, we can cover gaps in our understanding of the problem - its incompleteness.
#DataScience #ArtificialIntelligence #MachineLearning

https://hubs.li/H0yRBFJ0

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🗣 @AI_Python_arXiv
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What a Biden-Harris Administration means for artificial intelligence
https://bit.ly/3phQDwj

#ai #ArtificialIntelligence #MachineLearning #DeepLearning

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🗣 @AI_Python_arXiv
✴️ @AI_Python_en

Andrew Ng: What rules regarding publishing papers would be fair, when it relates to work done by researchers working for companies? I ask this question in this week's The Batch, and would love to hear your thoughts.

https://blog.deeplearning.ai/blog/the-batch-new-coronavirus-treatments-reimagining-robotaxis-opening-historical-archives-streamlining-simulations

#مقاله #منابع #هوش_مصنوعی
#AI #ArtificialIntelligence

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_En

آموزش های هوش مصنوعی دکتر اله یاری

RNN and LSTM Networks Tutorial Part 1

#منابع #فیلم #دانشگاه #الگوریتمها #کلاس_آموزشی #یادگیری_ماشین #هوش_مصنوعی
#machinelearning #ArtificialIntelligence #DeepLearning

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN

آموزش های هوش مصنوعی دکتر اله یاری

RNN and LSTM Networks Tutorial Part 1

#منابع #فیلم #دانشگاه #الگوریتمها #کلاس_آموزشی #یادگیری_ماشین #هوش_مصنوعی
#machinelearning #ArtificialIntelligence #DeepLearning

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN

کلاس آموزش هوش مصنوعی (جلسه دهم) دانشگاه تبریز - دکتر رضوی - روش‌های جستجوی محلی و الگوریتم تپه‌نوردی

🔸 معرفی و ایده روش‌های جستجوی محلی
🔸 الگوریتم تپه‌نوردی
🔸 اجرای مرحله به مرحله تپه‌نوردی برای حل مسئله هشت-وزیر
🔸 پیاده‌سازی در پایتون و اجرای نمایشی تپه‌نوردی
#هوش_مصنوعی #منابع #فیلم #دکتر_رضوی #کلاس_آموزشی #آموزش_کلاسی #ai #artificialintelligence
🌎 وب‌سایت درس
🌎 Link Review

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🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

دانلود رایگان کتاب مقدمه ای بر علم داده: یادگیری زبان جولیا و با دیدگاهی بر ریاضیات در علم داده

1, Vectors
2. Matrices
3. Sigmoid
4. K Means Clustering
5. Gradient Descent

https://datascience-book.gitlab.io/

#کتاب #علم_داده #منابع
#DataScience #MachineLearning #ArtificialIntelligence #JuliaLang

❇️ @AI_Python

for AI researchers.

Here are some of the papers I really liked

1. Text generation with GAN's

https://lnkd.in/f8fb9zC

2. Unsupervised image to image translation

https://lnkd.in/fJnvacb

3. Deep nets with box convolutions.

https://lnkd.in/fum8ded

4.middle out decoding

https://lnkd.in/fkGBGqr

#مقاله
#machinelearning #deeplearning #artificialintelligence #computervision #nlp #neuralnetworks


✴️ @AI_Python_EN
❇️ @AI_Python

بهترین منابع یادگیری عمیق : پروژه های نهایی دانشجویان دانشگاه استنفورد

https://lnkd.in/eA843qV

#machinelearning #deeplearning #artificialintelligence #DL #ML #AI
#منابع #آموزش #یادگیری_عمیق

🌎 Link Review

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN

Very interesting idea on how to move 'common sense' in AI forward. It is always great to explore different ideas and directions and have different perspectives to increase chances of success and advancement.
https://www.technologyreview.com/2022/06/24/1054817/yann-lecun-bold-new-vision-future-ai-deep-learning-meta/

#ai #ml #dl #artificialintelligence #machinelearning #deeplearning

Machine Learning on Geographical Data

#Geodata #ML #MachineLearning #Python
#AI #DataScience #artificialIntelligence

https://reconshell.com/machine-learning-on-geographical-data/

اصطلاح data-drift یا dataset drift که در فارسی به جابجایی داده یا رانش داده ترجمه می‌شود زمانی اتفاق می‌افتد که مجموعه داده مورد استفاده در آموزش مدل تفاوت زیادی با داده‌هایی که در زمان استقرار یا محیط عملیاتی ( اصطلاحا deploy یا production) مشاهده خواهد شد دارد و در نتیجه مدل شما نتایج نامطلوب و عجیب ایجاد کرده و عملکرد ضعیفی دربرخواهد داشت.

در مقاله‌ای جدید، تیمی از محققان روش خاصی را برای برخورد با این مشکل در زمینه داده‌های تصویری ارائه کردند:

"Data Models for Dataset Drift Controls in Machine Learning With Images"

Paper: https://arxiv.org/abs/2211.02578
Code: https://github.com/aiaudit-org/raw2logit
Dataset: https://paperswithcode.com/dataset/raw-microscopy-and-raw-drone

#MachineLearning #DeepLearning #ArtificialIntelligence #ML #DL #AI


#یادگیری_ماشین #مقاله

✳️ @AI_Python