• Practical Deep Learning Course - Frontend Master

  • Basic Machine Learning

    • Linear Regression

  • Basic Nueral Network and Cnovolution NN:

    • Basic Nueral Network on MNIST
    • Implement PCA on MNIST Dataset
    • Implement Basic Convolution Nueral Network
    • Raw Implementation of Filter/Kernel & MaxPooling without use of TF
    • Create Stylist Image with Combination of Two Images
    • Transfer Learning - Use already trained model

  • Basic Natural Language Processing:

    • One Hot Encoding IMDB reviews with Keras
    • Word Embedding on IMDB reviews
    • Basic Sentimental Analysis on IMDB reviews
    • LSTM for Predicting Author of a Text

• Medical RAG

  • RAG system Implemented by Pytorch From Scratch:
    • Training Embedding model:
      • Fine-tunes the BioClinical BERT model on the MEDMCQA dataset. (25 epochs, 40k dataset, Kaggle run (2 T4 GPU)) --> around 4 hour run
    • Preprocessed Dataset:
      • cleaned dataset and save it as a json
    • Fine-tuned t5-small:
      • Fine-tuned model by using a adapter layer
    • Implemented RAG:
      • Done Evaluation on the RAG results
  • Worked with HuggingFace: push dataset, push model weights
  • Worked with Kaggle
  • Documented the Process and Challenges

• RAG from Scratch with LangChain

  • Worked with Environments Variables
  • Worked with LangChain Libraries
  • Worked with AvalAI API
  • Worked with ChromaDB (Vector Database)

• Neural Network From Scratch with Numpy

  • Implementation of Neural Network by using only Numpy and Python Functions:
    • ReLU (Rectified Linear Unit)
    • Feed-Forward
    • Back-Propagation
    • Gradient-Descent
    • One-Hot-Encoding
    • Get-Prediction
    • Get-Accuracy

• My Python Exercise

  • Fluent-Python Codes
  • MIT Finger-Exercises + Problem Sets:
    • Basic Understandings of Programming, Computer Science and Python:
      • Different Data Types: int, float, str, list, tuple, dictionary, sets
        • Comprehensions
        • Alias
        • Copy
      • Control Flow:
        • Branching: if, elif, else
        • Loop/Iteration: for, while
          • Break statement
      • Functions:
        • Abstraction
        • Decomposition
        • Lambda Function
        • Function Scope/Environments
      • OOP:
      • Classes in Python:
        • Inheritence
        • Dunder Functions / Magic Method
        • Getter/Setter
      • Testing/Validation
        • Unit Test
        • Regression Test
        • Integration Test
      • Debugging
      • Exception
        • Try, Except, Assertion
      • Recursion
      • Basic Algorithms:
        • Timing & Runtime
        • Guess & Check
        • Approximation Algorithms
          • Bisection-Search
          • Newton-Raphson
        • Sorting Algorithms
          • Bogo Sort
          • Bubble Sort
          • Selection Sort
          • Merge Sort
        • Search Algorithms
      • Mathplotlib: Visualization with Python
      • Running Simulations
    • Calorie Tracking Program
      • OOP
      • Abstraction + Decomposition
      • Functions
    • Implemented Hangman Game
      • Functions
  • Randoms:
    • AvalAi API
    • Playing with Browser
    • Working with HuggingFace API
    • Worked with Database (Sqlite) through Python
    • Getting System Info with Python
    • Worked with files with Python
      • Move, Unzip, Open, etc.

• Smart-Feed

  • Understanding of Python Development Environments
    • UV tool
    • Ruff Formatter & Linter
    • Commitizen
    • Pre-commit
    • Makefile
    • Github Actions
    • Documentation

• General Notes Contain Notes/Documents/Summary on General Concepts, like:

• How to read Math

  • How to read Math V1|The Math Sorcerer - How to read Math - Old version
  • How to read Math V2|The Math Sorcerer - How to read Math - Newer version

• How to Speak

  • How to Speak|MIT - How to Speak
    • How to Speak#How to start Presentation?|How to start Presentation
    • How to Speak#Boards, Props, Slides|Boards, Props, Slides
    • How to Speak#Informing Presentation|Informing Presentation
    • How to Speak#Persuading|Persuading
      • How to Speak#Oral Exams(Thesis Session...)|Oral Exams - Thesis Presentation
      • How to Speak#Job Talks|Job Interview
      • How to Speak#Getting Famous|Getting Famous
    • How to Speak#How to Stop|How to Finish our Presentation
  • Communication Techniques|Stanford - Think Fast, Talk Smart
    • Communication Techniques#Anxiety Management|Anxiety Management
      • Communication Techniques#Techniques to handle Anxiety|Techniques to handle Anxiety
    • Communication Techniques#How to feel Comfortable when you Speaking Spontaneously|How to feel comfortable when speaking techniques

• 10 Fast Finger

  • How to learn 10 finger Typing

• Learn Obsidian

  • Leran Obsidian

• Interview & Resume

  • How to write a Resume

• AI & Computer Notes Contain Notes/Documents/Summary on Computer & AI Concepts, like:

• Tools

  • Git
    • Primeagen Git

• Python

  • MIT-Python
  • Practical-Python

• Editor

  • VIM
  • NeoVim
    • Kickstart TJ
    • Primeagen

• Artificial Intelligence

  • Machine Learning
    • Course
      • Abu Yaser-Mostafa Course Content List

• Computer Science Concepts

  • Distributed Systems
    • Docker