Leanpub

Leanpub

Users
Tweets

Leanpub

@leanpub

Jun 11

Mastering Ontology Engineering with Protégé and Pizza.owl: From Semantic Foundations to Executable Knowledge Architecture (EKA) by Xiaoqi Zhao is the featured book 📖 on Leanpub! Transform the classic pizza.owl tutorial into a launchpad for cutting-edge semantic engineering! This hands-on guide bridges the gap between theory and practice, showing you exactly how to build ontology-based meta-models and deploy executable knowledge graphs. Master the "Diagramming as Code" methodologies of the Executable Knowledge Architecture (EKA) framework through a continuous, live-updated learning journey. #computer_programming #ai #data_structures #software_architecture #software_engineering

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Leanpub

Leanpub

@leanpub

May 1

Rust Programming MasterClass (Updated 2026) by GitforGits | Asian Publishing House is the featured bundle of ebooks 📚 on Leanpub! Build, test, and package Rust the professional way, then accelerate with 100 practical solutions across performance, CI/CD, and service-style patterns. Add network programming and automation skills, including protocols and packet analysis, so our Rust can power real infrastructure. #rust #data_structures #software_engineering #distributed_systems #apis #computer_hardware #networking #programming_cookbooks #computer_security #operating_system_development

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Tech with Mak

Tech with Mak

@techNmak

Feb 25

This repo is basically a CS degree. For free. The Algorithms - Python. 218K GitHub stars. Every algorithm you'd learn in 4 years of computer science. All in one place. Just look at the categories inside. 👇 maths sorts graphs hashes matrix ciphers geodesy physics quantum strings fractals geometry graphics knapsack searches financial blockchain scheduling conversions electronics fuzzy_logic backtracking audio_filters file_transfer project_euler greedy_methods linear_algebra neural_network boolean_algebra computer_vision data_structures networking_flow web_programming bit_manipulation data_compression machine_learning cellular_automata genetic_algorithm divide_and_conquer linear_programming dynamic_programming digital_image_processing Every implementation is: → Clean and readable → Well-documented with docstrings → Annotated with type hints → Includes Big O complexity Purely written for learning, exploring, and tinkering. ➡️ Open it. ➡️ Star it. ➡️ Thank me later. The best CS education is free and on GitHub. Link in comments.

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16,002

Tech with Mak

Tech with Mak

@techNmak

Jan 13

If you’re into Python (or even just pretending to be 😏)… there’s a repo you cannot afford to sleep on. It’s called The Algorithms - Python. 👉Every algorithm you’ve ever read about (and 100 more you haven’t), implemented in Python. Just look at the categories inside 👇 maths sorts graphs hashes matrix ciphers geodesy physics quantum strings fractals geometry graphics knapsack searches financial blockchain scheduling conversions electronics fuzzy_logic backtracking audio_filters file_transfer project_euler greedy_methods linear_algebra neural_network boolean_algebra computer_vision data_structures networking_flow web_programming bit_manipulation data_compression machine_learning cellular_automata genetic_algorithm divide_and_conquer linear_programming dynamic_programming digital_image_processing Purely written for learning, exploring, and tinkering. 📚You want to actually understand how algorithms work? This repo is a goldmine. 💡You want to flex by dropping rare algorithm knowledge in code reviews? This is your ammo. ➡️Open it. ➡️Star it. ➡️Thank me later. GitHub repo is in the comments. ♻️Repost to save someone $$$ and a lot of confusion. ✔️You can follow @techNmak , for more insights.

2,163

Tech with Mak

Tech with Mak

@techNmak

25 Dec 2025

If you’re into Python (or even just pretending to be 😏)… there’s a repo you cannot afford to sleep on. It’s called The Algorithms - Python. 👉 Every algorithm you’ve ever read about (and 100 more you haven’t), implemented in Python. Just look at the categories inside 👇 maths sorts graphs hashes matrix ciphers geodesy physics quantum strings fractals geometry graphics knapsack searches financial blockchain scheduling conversions electronics fuzzy_logic backtracking audio_filters file_transfer project_euler greedy_methods linear_algebra neural_network boolean_algebra computer_vision data_structures networking_flow web_programming bit_manipulation data_compression machine_learning cellular_automata genetic_algorithm divide_and_conquer linear_programming dynamic_programming digital_image_processing Purely written for learning, exploring, and tinkering. 📚 You want to actually understand how algorithms work? This repo is a goldmine. 💡 You want to flex by dropping rare algorithm knowledge in code reviews? This is your ammo. ➡️ Open it. ➡️ Star it. ➡️ Thank me later. GitHub repo is in the comments. ♻️ Repost to save someone $$$ and a lot of confusion. ✔️ You can follow @techNmak, for more insights.

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Dhanian 🗯️

Dhanian 🗯️

@e_opore

16 Dec 2025

LLMs Roadmap ├── 01_Foundations │ ├── Programming_Basics │ │ ├── Python_for_AI │ │ │ ├── Data_Types_Functions_Modules │ │ │ ├── Virtual_Environments_Packages │ │ │ └── Real_Project │ │ │ └── Build_a_Text_File_Analyzer │ ├── Math_for_LLMs │ │ ├── Linear_Algebra_Basics │ │ ├── Probability_and_Statistics │ │ └── Intuition_Focused_Learning │ └── Computer_Science_Fundamentals │ ├── Data_Structures │ ├── Algorithms_Basics │ └── Complexity_Thinking │ ├── 02_Machine_Learning_Core │ ├── ML_Concepts │ │ ├── Supervised_vs_Unsupervised │ │ ├── Training_vs_Inference │ │ └── Overfitting_Underfitting │ ├── Tools │ │ ├── NumPy_Pandas │ │ ├── Scikit_Learn │ │ └── Matplotlib │ └── Real_Project │ └── Build_a_Text_Classifier_for_Support_Tickets │ ├── 03_Neural_Networks │ ├── Core_Concepts │ │ ├── Neurons_Layers_Activations │ │ ├── Backpropagation │ │ └── Loss_Functions │ ├── Frameworks │ │ ├── PyTorch │ │ └── TensorFlow │ └── Real_Project │ └── Build_a_Sentiment_Analysis_Model │ ├── 04_NLP_Foundations │ ├── Text_Processing │ │ ├── Tokenization │ │ ├── Stopwords_Stemming_Lemmatization │ │ └── Vectorization │ ├── Language_Models_Before_LLMs │ │ ├── N_Grams │ │ ├── Word2Vec_GloVe │ │ └── Limitations │ └── Real_Project │ └── Build_a_Smart_Search_Engine_for_Documents │ ├── 05_Transformers_and_LLM_Core │ ├── Transformer_Architecture │ │ ├── Self_Attention │ │ ├── Multi_Head_Attention │ │ ├── Positional_Encoding │ │ └── Encoder_vs_Decoder │ ├── Popular_LLMs │ │ ├── GPT_Family │ │ ├── LLaMA │ │ ├── Mistral │ │ └── Claude │ └── Real_Project │ └── Build_a_Mini_GPT_Text_Generator │ ├── 06_LLM_Usage_and_Engineering │ ├── Prompt_Engineering │ │ ├── Zero_Shot │ │ ├── Few_Shot │ │ ├── Chain_of_Thought │ │ └── System_Prompts │ ├── LLM_APIs │ │ ├── OpenAI_API │ │ ├── HuggingFace_Inference │ └── Real_Project │ └── Build_an_AI_Study_Assistant ├── 07_Retrieval_Augmented_Generation_RAG │ ├── Core_Idea │ │ ├── Embeddings │ │ ├── Vector_Databases │ │ └── Context_Injection │ ├── Tools │ └── Real_Project │ └── Build_a_Custom_Knowledgebase_Chatbot ├── 08_Fine_Tuning_and_Optimization │ ├── Fine_Tuning │ ├── Evaluation │ └── Real_Project │ └── Fine_Tune_an_LLM_for_Customer_Support │ ├── 09_AI_Agents_and_Tools │ ├── Agent_Concepts │ ├── Frameworks │ │ ├── LangChain │ └── Real_Project │ └── Build_an_AI_Agent_that_Automates_Research ├── 10_Deployment_and_Production │ ├── Model_Serving │ │ ├── FastAPI │ │ ├── Docker │ │ └── GPU_Usage │ ├── Cloud │ │ ├── AWS_GCP_Azure │ │ ├── Serverless_AI │ │ └── Cost_Optimization │ └── Real_Project │ └── Deploy_an_AI_Chat_App_for_Real_Users ├── 11_Responsible_and_Modern_AI │ ├── Ethics │ ├── Security/ │ └── Real_Project │ └── Secure_and_Monitor_an_LLM_Based_System └── 12_Capstone_Real_World_AI_Product ├── Idea │ ├── AI_SaaS │ ├── AI_Tutor │ ├── AI_Coding_Assistant │ └── AI_Business_Analytics_Tool ├── Build │ ├── End_to_End_System │ ├── Scalable_Architecture │ └── Real_User_Feedback └── Outcome └── Production_Ready_LLM_Product Grab this Ebook resource to deepen your LLM journey: codewithdhanian.gumroad.com/…

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