Forwarded from Machine Learning with Python
Auto-Encoder & Backpropagation by hand ✍️ lecture video ~ 📺 https://byhand.ai/cv/10
It took me a few years to invent this method to show both forward and backward passes for a non-trivial case of a multi-layer perceptron over a batch of inputs, plus gradient descents over multiple epochs, while being able to hand calculate each step and code in Excel at the same time.
= Chapters =
• Encoder & Decoder (00:00)
• Equation (10:09)
• 4-2-4 AutoEncoder (16:38)
• 6-4-2-4-6 AutoEncoder (18:39)
• L2 Loss (20:49)
• L2 Loss Gradient (27:31)
• Backpropagation (30:12)
• Implement Backpropagation (39:00)
• Gradient Descent (44:30)
• Summary (51:39)
✉️ Our Telegram channels: https://t.iss.one/addlist/0f6vfFbEMdAwODBk
It took me a few years to invent this method to show both forward and backward passes for a non-trivial case of a multi-layer perceptron over a batch of inputs, plus gradient descents over multiple epochs, while being able to hand calculate each step and code in Excel at the same time.
= Chapters =
• Encoder & Decoder (00:00)
• Equation (10:09)
• 4-2-4 AutoEncoder (16:38)
• 6-4-2-4-6 AutoEncoder (18:39)
• L2 Loss (20:49)
• L2 Loss Gradient (27:31)
• Backpropagation (30:12)
• Implement Backpropagation (39:00)
• Gradient Descent (44:30)
• Summary (51:39)
#AIEngineering #MachineLearning #DeepLearning #LLMs #RAG #MLOps #Python #GitHubProjects #AIForBeginners #ArtificialIntelligence #NeuralNetworks #OpenSourceAI #DataScienceCareers
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❤5
What is torch.nn really?
This article explains it quite well.
📌 Read
✉️ Our Telegram channels: https://t.iss.one/addlist/0f6vfFbEMdAwODBk
When I started working with PyTorch, my biggest question was: "What is torch.nn?".
This article explains it quite well.
📌 Read
#pytorch #AIEngineering #MachineLearning #DeepLearning #LLMs #RAG #MLOps #Python #GitHubProjects #AIForBeginners #ArtificialIntelligence #NeuralNetworks #OpenSourceAI #DataScienceCareers
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❤7
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🧠 By: https://t.iss.one/DataScienceM
📝 Description: Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models.
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❤3
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🌐 Website: https://googleapis.github.io/genai-toolbox/getting-started/introduction/
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🧠 By: https://t.iss.one/DataScienceM
📝 Description: Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen2.5, Qwen3, Llama, and more!
🔗 Repository URL: https://github.com/OpenPipe/ART
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🤖🧠 How oLLM Makes Large-Context AI Models Run Smoothly on 8GB GPUs
🗓️ 11 Oct 2025
📚 AI News & Trends
Artificial intelligence has revolutionized the way we process information, analyze data, and automate complex tasks. With the rise of large language models (LLMs), AI capabilities have grown exponentially, enabling applications from natural language understanding to multimodal reasoning. However, running these models efficiently especially with massive context windows, remains a challenge due to their high memory ...
#oLLM #LargeContextAI #AIGPU #MachineLearning #LLMs #AIOptimization
🗓️ 11 Oct 2025
📚 AI News & Trends
Artificial intelligence has revolutionized the way we process information, analyze data, and automate complex tasks. With the rise of large language models (LLMs), AI capabilities have grown exponentially, enabling applications from natural language understanding to multimodal reasoning. However, running these models efficiently especially with massive context windows, remains a challenge due to their high memory ...
#oLLM #LargeContextAI #AIGPU #MachineLearning #LLMs #AIOptimization
❤1
🤖🧠 Try Powerful Mem0 AI to build Long-Term Memory for AI Agents
🗓️ 12 Oct 2025
📚 AI News & Trends
Artificial Intelligence has made incredible leaps in recent years from chatbots that converse naturally to AI agents capable of reasoning and decision-making. However, one major limitation has persisted: memory. Traditional large language models (LLMs) like ChatGPT or Claude can process vast data but fail to remember context across long interactions. This is where Mem0 AI, ...
#Mem0AI #AIAgents #LongTermMemory #ArtificialIntelligence #AIMemory #LLMs
🗓️ 12 Oct 2025
📚 AI News & Trends
Artificial Intelligence has made incredible leaps in recent years from chatbots that converse naturally to AI agents capable of reasoning and decision-making. However, one major limitation has persisted: memory. Traditional large language models (LLMs) like ChatGPT or Claude can process vast data but fail to remember context across long interactions. This is where Mem0 AI, ...
#Mem0AI #AIAgents #LongTermMemory #ArtificialIntelligence #AIMemory #LLMs
🤖🧠 Ultimate OpenTSLM: Stanford’s Open-Source Framework Bridging LLMs and Medical Time-Series Data
🗓️ 13 Oct 2025
📚 AI News & Trends
In recent years, artificial intelligence (AI) has made remarkable strides in transforming healthcare. From medical imaging to patient monitoring systems, AI-driven solutions are reshaping how clinicians diagnose, treat and manage diseases. One of the most promising developments in this space is the integration of large language models (LLMs) with time-series data, a combination that holds ...
#OpenTSLM #LLMs #MedicalAI #TimeSeriesData #ArtificialIntelligence #OpenSourceFramework
🗓️ 13 Oct 2025
📚 AI News & Trends
In recent years, artificial intelligence (AI) has made remarkable strides in transforming healthcare. From medical imaging to patient monitoring systems, AI-driven solutions are reshaping how clinicians diagnose, treat and manage diseases. One of the most promising developments in this space is the integration of large language models (LLMs) with time-series data, a combination that holds ...
#OpenTSLM #LLMs #MedicalAI #TimeSeriesData #ArtificialIntelligence #OpenSourceFramework
🤖🧠 NVIDIA, MIT, HKU and Tsinghua University Introduce QeRL: A Powerful Quantum Leap in Reinforcement Learning for LLMs
🗓️ 17 Oct 2025
📚 AI News & Trends
The rise of large language models (LLMs) has redefined artificial intelligence powering everything from conversational AI to autonomous reasoning systems. However, training these models especially through reinforcement learning (RL) is computationally expensive requiring massive GPU resources and long training cycles. To address this, a team of researchers from NVIDIA, Massachusetts Institute of Technology (MIT), The ...
#QuantumLearning #ReinforcementLearning #LLMs #NVIDIA #MIT #TsinghuaUniversity
🗓️ 17 Oct 2025
📚 AI News & Trends
The rise of large language models (LLMs) has redefined artificial intelligence powering everything from conversational AI to autonomous reasoning systems. However, training these models especially through reinforcement learning (RL) is computationally expensive requiring massive GPU resources and long training cycles. To address this, a team of researchers from NVIDIA, Massachusetts Institute of Technology (MIT), The ...
#QuantumLearning #ReinforcementLearning #LLMs #NVIDIA #MIT #TsinghuaUniversity