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Why are Neural Network Activation Functions Non-Linear ?

📹 VIDEO TITLE 📹 Why are Neural Network Activation Functions Non-linear ? ✍️VIDEO DESCRIPTION ✍️ In this video, we begin by exploring what activation functions are and their pivotal role in neural networks. These mathematical equations are essential for determining the output of a neuron based on given inputs, introducing non-linearity into the model. This non-linearity is crucial as it allows the network to learn complex patterns and relationships in data, making sense of intricate information and adding flexibility to the model. Without activation functions, neural networks would be limited to modeling only linear relationships, significantly reducing their effectiveness. As we progress, we examine the limitations of linear activation functions and why most real-world applications prefer non-linear ones. Non-linear functions allow for multiple layers of transformation, essential for deep learning tasks like image and speech recognition. We also tintroduce other commonly used non-linear activation functions such as Sigmoid, Tanh, ReLU, and Softmax. Each of these functions has unique characteristics, making them suitable for different tasks and architectures. Stay tuned for more insights, with more videos, as we go futher with neural networks and their role in delivering powerful AI solutions. 📽OTHER NEW MACHINA VIDEOS REFERENCED IN THIS VIDEO 📽 Build an MP Neuron with PyTorch -    • Build an MP Neuron with PyTorch   LangChain versus LangGraph -    • LangChain versus LangGraph   Chroma versus Pinecone Vector Database -    • Chroma versus Pinecone Vector Database   What is the Chroma Vector Database ? -    • What is the Chroma Vector Database ?   RAG with OpenAI & Pinecone Vector Database ? -    • RAG with OpenAI & Pinecone Vector Database ?   What are LLM Function Calls ? -    • What are LLM Function Calls ?   Embeddings with Open AI & Pinecone Vector Database -    • Embeddings with Open AI & Pinecone Vector ...   What is Hugging Face? -    • What is Hugging Face ?   RAG vs Fine-Tuning -    • RAG versus LLM Fine-Tuning   What is RAG ? -    • What is RAG ?   What is the Perceptron? -    • What is the Perceptron ?   What is the MP Neuron? -    • What is the MP Neuron ?   What is Physical AI ? -    • What is Physical AI ?   What is the Turing Test ? -    • What is the Turing Test?   What is LLM Alignment ? -    • What is LLM Alignment ?   What are Agentic Workflows? -    • What are Agentic Workflows ?   What is Synthetic Data? -    • What is Synthetic Data?   What is NLP? -    • What is NLP ?   What is Open Router? -    • What is Open Router ?   What is Mojo ? -    • What is Mojo ?   SDK(s) in Pinecone Vector DB -    • SDK(s) in Pinecone Vector DB   Pinecone Vector DB POD(s) vs Serverless -    • Pinecone Vector Database PODS vs Serverless   Meta Data Filters in Pinecone Vector DB -    • Meta Data Filters in Pinecone Vector Database   Namespaces in Pinecone Vector DB -    • Meta Data Filters in Pinecone Vector Database   Fetches & Queries in Pinecone Vector DB -    • Meta Data Filters in Pinecone Vector Database   Upserts & Deletes in Pinecone Vector DB -    • Meta Data Filters in Pinecone Vector Database   What is a Pineconde Index -    • What is a Pinecone Index ?   What is the Pinecone Vector DB -    • What is a Pinecone Index ?   What is LLM LangGraph ? -    • What is LLM LangGraph?   AWS Lambda + Anthropic Claude -    • AWS Lambda + Anthropic Claude   What is Llama Index ? -    • What is LLM Llama Index ?   LangChain HelloWorld with Open GPT 3.5 -    • LangChain HelloWorld with Open GPT 3.5   Forget about LLMs What About SLMs -    • Forget about LLMs What About SLMs ?   What are LLM Presence and Frequency Penalties? -    • What are LLM Presence and Frequency Penalt...   What are LLM Hallucinations ? -    • What are LLM Hallucinations ?   Can LLMs Reason over Large Inputs ? -    • Can LLMs Effectively Reason over Large Inp...   What is the LLM’s Context Window? -    • What is the LLM's Context Window ?   What is LLM Chain of Thought Prompting? -    • What is LLM Chain of Thought Prompting?   Algorithms for Search Similarity -    • Algorithms for Search Similarity   How LLMs use Vector Databases -    • How LLMs use Vector Databases   What are LLM Embeddings ? -    • What are LLM Embeddings ?   How LLM’s are Driven by Vectors -    • How LLM’s are Driven by Vectors   What is 0, 1, and Few Shot LLM Prompting ? -    • What is 0, 1, and Few Shot LLM Prompting ?   What are the LLM’s Top-P and TopK ? -    • What are the LLM’s Top-P + Top-K ?   What is the LLM’s Temperature ? -    • What is the LLM’s Temperature ?   What is LLM Prompt Engineering ? -    • What is LLM Prompt Engineering ?   What is LLM Tokenization? -    • What is LLM Tokenization ?   What is the LangChain Framework? -    • What is the LangChain Framework?   🔠KEYWORDS 🔠 #ActivationFunctions #NeuralNetworks #NonLinearity #ModelFlexibility #LinearRelationships #NonLinearFunctions #StepFunction #HeavisideFunction #Sigmoid #Tanh #ReLU #Softmax #LearningProcess #NeuralArchitectures #WeightUpdate