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آموزش انواع رگرسیونها از دکتر مهدی اله یاری
Autoencoders Tutorial Part 3 final
#منابع #فیلم #دانشگاه #الگوریتمها #کلاس_آموزشی #یادگیری_ماشین #هوش_مصنوعی
#machinelearning #ArtificialIntelligence #DeepLearning
❇️ @AI_Python
Autoencoders Tutorial Part 3 final
#منابع #فیلم #دانشگاه #الگوریتمها #کلاس_آموزشی #یادگیری_ماشین #هوش_مصنوعی
#machinelearning #ArtificialIntelligence #DeepLearning
❇️ @AI_Python
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آموزش «آمار برای هوش مصنوعی » از دانشگاه CMU
Probability Part 1
#کلاس_آموزشی #فیلم #منابع #آمار #هوش_مصنوعی #یادگیری_ماشین
#machineLearning #ArtificialIntelligence
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Probability Part 1
#کلاس_آموزشی #فیلم #منابع #آمار #هوش_مصنوعی #یادگیری_ماشین
#machineLearning #ArtificialIntelligence
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Seq2seq Learning Example Part 1
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🗣 @AI_Python_arXiv
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Seq2seq Learning Example Part 1
#منابع #فیلم #دانشگاه #الگوریتمها #کلاس_آموزشی #یادگیری_ماشین #هوش_مصنوعی
#machinelearning #ArtificialIntelligence #DeepLearning
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Seq2seq Learning Example Part 2
#منابع #فیلم #دانشگاه #الگوریتمها #کلاس_آموزشی #یادگیری_ماشین #هوش_مصنوعی
#machinelearning #ArtificialIntelligence #DeepLearning
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Seq2seq Learning Example Part 2
#منابع #فیلم #دانشگاه #الگوریتمها #کلاس_آموزشی #یادگیری_ماشین #هوش_مصنوعی
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RNN and LSTM Networks Tutorial Part 1
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RNN and LSTM Networks Tutorial Part 1
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Forwarded from DLeX: AI Python (Farzad 🦅)
Data Warehouse Concepts.pdf
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همه چی در مورد انباره داده ها Data Warehouse
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Forwarded from AI, Python, Cognitive Neuroscience (Farzad 🦅)
Lecture Notes in Deep Learning: Feedforward Networks — Part 3 | #DataScience #MachineLearning #ArtificialIntelligence #AI
https://bit.ly/2Z2GgQY
https://bit.ly/2Z2GgQY
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Feedforward Networks — Part 3
The Backpropagation Algorithm
Forwarded from AI, Python, Cognitive Neuroscience (Farzad 🦅)
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
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