# Wiki ## Wiki - [About](https://aisuko.gitbook.io/wiki/home/readme.md) - [The GNU Hurd](https://aisuko.gitbook.io/wiki/freesoftware/the-gnu-hurd.md) - [The files extension](https://aisuko.gitbook.io/wiki/freesoftware/the-gnu-hurd/the-files-extension.md) - [Tutorial for starting](https://aisuko.gitbook.io/wiki/freesoftware/the-gnu-hurd/tutorial-for-starting.md) - [Continue Working for the Hurd](https://aisuko.gitbook.io/wiki/freesoftware/the-gnu-hurd/continue-working-for-the-hurd.md) - [cgo](https://aisuko.gitbook.io/wiki/freesoftware/the-gnu-hurd/cgo.md) - [Statically VS Dynamically binding](https://aisuko.gitbook.io/wiki/freesoftware/the-gnu-hurd/cgo/statically-vs-dynamically-binding.md): What is the difference between statically binding and dynamically loading a shared library in Go - [Different ways in binding](https://aisuko.gitbook.io/wiki/freesoftware/the-gnu-hurd/cgo/different-ways-in-binding.md): Using shared object binary file in go binding - [Segfault](https://aisuko.gitbook.io/wiki/freesoftware/the-gnu-hurd/cgo/segmentation-fault.md) - [Rust FFI](https://aisuko.gitbook.io/wiki/freesoftware/the-gnu-hurd/rust-ffi.md): Rust Foreign Function Interface - [Programming](https://aisuko.gitbook.io/wiki/freesoftware/programming.md) - [Introduction to programming](https://aisuko.gitbook.io/wiki/freesoftware/programming/introduction-to-6811-programming.md) - [Mutable Value Semantics](https://aisuko.gitbook.io/wiki/freesoftware/programming/mutable_value_semantics.md) - [Linked List](https://aisuko.gitbook.io/wiki/freesoftware/programming/linked-list.md) - [Rust](https://aisuko.gitbook.io/wiki/freesoftware/programming/rust.md) - [Keyword dyn](https://aisuko.gitbook.io/wiki/freesoftware/programming/rust/keyword_dyn.md) - [Tonic framework](https://aisuko.gitbook.io/wiki/freesoftware/programming/rust/tonic.md) - [Tokio](https://aisuko.gitbook.io/wiki/freesoftware/programming/rust/tokio.md) - [Rust read files](https://aisuko.gitbook.io/wiki/freesoftware/programming/rust/read_files.md) - [Algorithm](https://aisuko.gitbook.io/wiki/freesoftware/algorithm.md) - [Two-pointer Technique](https://aisuko.gitbook.io/wiki/freesoftware/algorithm/two_pointer_technique.md) - [Linear Search Technique](https://aisuko.gitbook.io/wiki/freesoftware/algorithm/linear_search_technique.md) - [Binary Search Technique](https://aisuko.gitbook.io/wiki/freesoftware/algorithm/binary_search_technique.md) - [Counter Technique](https://aisuko.gitbook.io/wiki/freesoftware/algorithm/counter_technique.md) - [In Place Technique](https://aisuko.gitbook.io/wiki/freesoftware/algorithm/in_place_technique.md) - [Prefix Sum Technique](https://aisuko.gitbook.io/wiki/freesoftware/algorithm/prefix_sum_technique.md) - [N D Array](https://aisuko.gitbook.io/wiki/freesoftware/algorithm/nd_array.md) - [Sliding Window Technique](https://aisuko.gitbook.io/wiki/freesoftware/algorithm/sliding_window_technique.md) - [Juggling Technique](https://aisuko.gitbook.io/wiki/freesoftware/algorithm/juggling_technique.md) - [Chain](https://aisuko.gitbook.io/wiki/ai-techniques/chain.md) - [LangChain](https://aisuko.gitbook.io/wiki/ai-techniques/chain/langchain.md): lang-chain is a technique for adapting large language models (LLMs) to specific tasks. - [Concepts](https://aisuko.gitbook.io/wiki/ai-techniques/chain/langchain/concepts.md) - [Models](https://aisuko.gitbook.io/wiki/ai-techniques/chain/langchain/models.md) - [Prompts](https://aisuko.gitbook.io/wiki/ai-techniques/chain/langchain/prompts.md) - [Memory](https://aisuko.gitbook.io/wiki/ai-techniques/chain/langchain/memory.md) - [Indexes](https://aisuko.gitbook.io/wiki/ai-techniques/chain/langchain/indexes.md) - [framework](https://aisuko.gitbook.io/wiki/ai-techniques/framework.md) - [pytorch](https://aisuko.gitbook.io/wiki/ai-techniques/framework/pytorch.md) - [Time components](https://aisuko.gitbook.io/wiki/ai-techniques/framework/ml_training_components.md) - [burn](https://aisuko.gitbook.io/wiki/ai-techniques/framework/burn.md) - [Adaptation](https://aisuko.gitbook.io/wiki/ai-techniques/adaptation.md) - [LoRA](https://aisuko.gitbook.io/wiki/ai-techniques/adaptation/lora.md): Low-Rank Adaptation of Large Language Models. It is a promising technique for adapting LLMs to specific tasks in a computationally efficient manner. - [Matrix Factorization](https://aisuko.gitbook.io/wiki/ai-techniques/adaptation/lora/matrix-factorization.md) - [SVD](https://aisuko.gitbook.io/wiki/ai-techniques/adaptation/lora/svd.md): Singular Value Decomposition(A mathematical technique) - [Distillation of SVD](https://aisuko.gitbook.io/wiki/ai-techniques/adaptation/lora/svd/distillation-of-svd.md): A machine learning technique that uses SVD. - [Eigenvalues of a covariance matrix](https://aisuko.gitbook.io/wiki/ai-techniques/adaptation/lora/svd/eigenvalues-of-a-covariance-matrix.md) - [Eigenvalues](https://aisuko.gitbook.io/wiki/ai-techniques/adaptation/lora/svd/eigenvalues-of-a-covariance-matrix/eigenvalues.md) - [Covariance Matrix](https://aisuko.gitbook.io/wiki/ai-techniques/adaptation/lora/svd/eigenvalues-of-a-covariance-matrix/covariance-matrix.md) - [Checkpoint](https://aisuko.gitbook.io/wiki/ai-techniques/adaptation/lora/checkpoint.md) - [PEFT](https://aisuko.gitbook.io/wiki/ai-techniques/adaptation/peft.md): State-of-the-art Parameter-Efficient Fine-Tuning methods - [Training](https://aisuko.gitbook.io/wiki/ai-techniques/training.md) - [Training with QLoRA](https://aisuko.gitbook.io/wiki/ai-techniques/training/training-with-qlora.md): Fine-tuning models on consumer hardware - [Deep Speed](https://aisuko.gitbook.io/wiki/ai-techniques/training/deepspeed.md) - [Stable Diffusion](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion.md) - [Stable Diffusion model](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/stable-diffusion-model.md) - [Stable Diffusion v1 vs v2](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/stable-diffusion-v1-vs-v2.md) - [The important parameters for stunning AI image](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/the-important-parameters-for-stunning-ai-image.md) - [Diffusion in image](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/diffusion-in-image.md): Diffusion processing in image - [Classifier Free Guidance](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/classifier-free-guidance.md) - [Denoising strength](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/denoising-strength.md) - [Stable Diffusion workflow](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/stable-diffusion-workflow.md) - [LoRA(Stable Diffusion)](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/lora-stable-diffusion.md) - [Depth maps](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/depth-maps.md): Depth to image - [CLIP](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/clip.md) - [Embeddings](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/embeddings.md): The textual inversion - [VAE](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/vae.md): VAE stands for variational autoencoder - [Conditioning](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/conditioning.md) - [Diffusion sampling/samplers](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/diffusion-sampling-samplers.md) - [Prompt](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/prompt.md) - [ControlNet](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/controlnet.md) - [Settings Explained](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/controlnet/settings-explained.md): Explaining the ControlNet settings - [ControlNet with models](https://aisuko.gitbook.io/wiki/ai-techniques/stable-diffusion/controlnet/controlnet-with-models.md) - [Large Language Model](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model.md): Large language model - [SMID](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model/smid.md): Single Instruction Multiple Data - [ARM NEON](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model/arm-neon.md) - [Metal](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model/metal.md) - [BLAS](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model/blas.md): Basic Linear Algebra Subprograms - [ggml](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model/ggml.md): How to use quantization to democratize access to LLMs? - [llama.cpp](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model/llama.cpp.md): Port of Facebook's LLaMA model in C/C++ - [Measuring model quality](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model/measuring-model-quality.md) - [Type for NNC](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model/type-for-nnc.md): Type for neural network computations - [Token](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model/token.md) - [Doc Retrieval && QA with LLMs](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model/doc_retrieval_and_qa_llms.md): Generative AI - Document Retrieval and Question Answering with LLMs(Apply LLMs to the domain-specific data) - [Hallucination(AI)](https://aisuko.gitbook.io/wiki/ai-techniques/large-language-model/hallucination.md) - [diffusers](https://aisuko.gitbook.io/wiki/ai-techniques/diffusers.md): Hugging face diffusers and it allows one to customize the inage generation pipeline. - [Deconstruct the Stable Diffusion pipeline](https://aisuko.gitbook.io/wiki/ai-techniques/diffusers/deconstruct_sd_pipeline.md) - [diffusers](https://aisuko.gitbook.io/wiki/implementing/diffusers.md) - [The Annotated Diffusion Model](https://aisuko.gitbook.io/wiki/implementing/diffusers/the_annotated_diffusion_model.md) - [Trending](https://aisuko.gitbook.io/wiki/trending/trending.md) - [Vector database](https://aisuko.gitbook.io/wiki/trending/trending/vector_database.md) - [Programming Languages](https://aisuko.gitbook.io/wiki/trending/trending/programming_languages.md) - [Go & Rust manage their memories](https://aisuko.gitbook.io/wiki/trending/trending/programming_languages/go_rust_manage_their_memories.md) - [Performance of Rust and Python](https://aisuko.gitbook.io/wiki/trending/trending/programming_languages/performance_of_rust.md) - [Rust ownership and borrowing](https://aisuko.gitbook.io/wiki/trending/trending/programming_languages/rust_ob_with_hm_vec.md) - [Neural Network](https://aisuko.gitbook.io/wiki/trending/trending/neural_network.md) - [Sliding window/convolutional filter](https://aisuko.gitbook.io/wiki/trending/trending/neural_network/sliding_window.md) - [Quantum Machine Learning](https://aisuko.gitbook.io/wiki/trending/trending/quantum_machine_learning.md) - [Courses Collection](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection.md) - [Academic In IT](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/academic-in-it.md) - [Reflective Writing](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/academic-in-it/reflective-writing.md) - [UCB](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/ucb_courses.md) - [CS 61A](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/ucb_courses/cs_61a.md) - [Computer Science](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/ucb_courses/cs_61a/computer-science.md) - [Scheme](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/ucb_courses/cs_61a/scheme.md) - [Python](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/ucb_courses/cs_61a/python.md) - [Data Abstraction](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/ucb_courses/cs_61a/data-abstraction.md) - [Object-Oriented Programming](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/ucb_courses/cs_61a/object-oriented-programming.md) - [Interpreters](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/ucb_courses/cs_61a/interpreters.md) - [Streams](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/ucb_courses/cs_61a/streams.md) - [MIT Algorithm Courses](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses.md): This page is the cover for MIT algorithm courses - [MIT 18.01](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-18.01.md) - [Limits and continuity](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-18.01/limits.md) - [Derivatives](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-18.01/derivatives.md) - [Integrals](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-18.01/integrals.md) - [MIT 6.042J](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.042j.md): Also known as Mathematics for Computer Science - [Number Theory](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.042j/number-theory.md) - [Graph Theory](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.042j/graph-theory.md): Graph Theory is a fundamental field of mathematics - [Graph and Trees](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.042j/graph-theory/graph-and-trees.md) - [Shortest Paths and Minimum Spanning Trees](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.042j/graph-theory/shortest-paths-and-minimum-spanning-trees.md) - [MIT 6.006](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.006.md) - [Intro and asymptotic notation](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.006/intro-and-asymptotic-notation.md) - [Sorting and Trees](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.006/sorting-and-trees.md) - [Sorting](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.006/sorting-and-trees/sorting.md) - [Trees](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.006/sorting-and-trees/trees.md) - [Hashing](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.006/hashing.md) - [Graphs](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.006/graphs.md) - [Shortest Paths](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.006/shortest-paths.md) - [Dynamic Programming](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.006/dynamic-programming.md) - [Advanced](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.006/advanced.md) - [MIT 6.046J](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.046j.md): Design and Analysis of Algorithms - [Divide and conquer](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.046j/divide-and-conquer.md) - [Dynamic programming](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.046j/dynamic-programming.md) - [Greedy algorithms](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.046j/greedy-algorithms.md) - [Graph algorithms](https://aisuko.gitbook.io/wiki/courses-collection/courses-collection/mit-algorithm-courses/mit-6.046j/graph-algorithms.md)