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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.

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.

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.

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/…

صباح الأنجاز 💗💗. #هندسة_حاسب #جامعة_الطائف #Data_Structures

مبرمجين ذو كفاءة عالية لحل المشاريع #Asp_net #C_sharb #java #programming #php #web_application #html_css #data_structures #database #sql_server #Mysql #هندسة_برمجيات #برمجة_سي_شارب #جافا #برمجة_سي_بلس_بلس #برمجة_شيئية #السعودية

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Stack using Linked List ✅ هيكل خفيف لطيف نظامه بكل بساطة يعتمد على LIFO (Last in First out) بمعنى الاضافة والحذف يكون من أعلى الهيكل 🔝 كتبته باستعمال ال Linked List وكان سهل وبسيط، ممكن اكتبه باستعمال ال Array مستقبلا احسها أعقد . الرابط تلاقوه بالمثبتة #data_structures

📍لمّا تتعامل مع تراكيب البيانات فإن الأهم هو فهم كيف يعمل كل هيكل، متى تستخدمه، وليش يُفضل على غيره في مواقف معينة👩‍💻💯. طيب كيف نفهم المنطق بدلاً من انو نحفظ الكود؟🤔⁉️ تصور التركيب: حاول رسم الهيكل على الورق وفهم كيفية تخزين البيانات داخله. افهم العمليات الأساسية: ما تكتفِ بكتابة insert() أو delete()، بل افهم كيف تتم العمليات خطوة بخطوة. حلّل التعقيد الزمني: اسأل نفسك دائمًا، هل هذا الحل O(1) أو O(n) أو O(log n)؟ اكتب الكود من الصفر: لا تعتمد على النسخ واللصق، بل حاول كتابة الكود من فهمك الشخصي. طبّق في مشاريع حقيقية إذا فهمت المنطق، بتقدر تكتب الكود بأي لغة برمجة من غير ما تحتاج لحفظه!💯✅ #رمضان #تراكيب_بيانات #data_structures