abdullahabdelhakeem6484 Goto Github PK

house-prices-advanced-regression-techniques_iti

house-prices-advanced-regression-techniques

investigating-netflix-movies-and-guest-stars-in-the-office---datacamp

Investigating Netflix Movies and Guest Stars in The Office -Data Scientist Track - DataCamp

iti_g3_efficient_intel

iti_graduation_project1_sisr_by_gan

Graduation Project 1 ITI_BrightSkies Single Image Super Resolution by SRGAN

javamachinelearningprojectiti

Machine Learning Project Java Programming Language (Webservices and Tester Client )

machine-learning-mathematics

Machine-Learning-Mathematics

machine-learning-model-diabetes-prediction-with-dashboard-iti-

Machine Learning prediction Model with Data visualization by Dash, Plotly, flask, html, CSS,JS and Python (AI_PRO Intake 1 @ ITI)

ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

mod2-solution

module2-solution

mod4_solution

mod4_solution

mod5-solution

Mod5-Solution

mod5_solution

mod5_solution

module2-solution

Coursera Module 2 Coding Assignment

module3-solution

module3-solution

module3-solution.github.io

module3-solution

module4-solution

module4-solution

module5-solution

module5-solution

myonline_certificates

Coursera-Udemy-Udacity-Edx-ITI-Edrak..etc

nlp-to-translate-data-science-content-into-arabic-

NLP to Translate Data Science Content into Arabic

numerical-optimization-projects-iti

BATCH GD - MINI BATCH GD - STOCHASTIC GD -MOMENTUM Based - NESTROV - ADAGRAD - RMSP PROB- ADAM . During logistic regression, in order to compute the optimal parameters in the model, we have to use an iterative numerical optimization approach (Newton method or Gradient descent method, instead of a simple analytical approach). Numerical optimization is a crucial mathematical concept in machine learning and function fitting, and it is deeply integrated in model training, regularization, support vector machine, neural network, and so on. In the next few posts, I will summarize key concepts and approaches in numerical optimization, and its application in machine learning.

oscilloscope-stm32f

Oscilloscope-STM32F

plagiarism-detection-model---ml-nanodegree

Plagiarism Detection Model - This task will be broken down into a few discrete steps: Upload your data to S3. Define a binary classification model and a training script. Train your model and deploy it. Evaluate your deployed classifier and answer some questions about your approach.

predicting-credit-card-approvals---datacamp

Predicting Credit Card Approvals - Data Scientist Track - DataCamp

project-1-automatic-review-analyzer

Project 1: Automatic Review Analyzer

project-dr.-semmelweis-and-the-discovery-of-handwashing---datacamp

Project Dr. Semmelweis and the Discovery of Handwashing - Data Scientist Track - DataCamp

project-the-android-app-market-on-google-play---datacamp

Project The Android App Market on Google Play - Data Scientist Track - DataCamp

readme_abdullah

scikit-learn

scikit-learn: machine learning in Python

sentiment_analysis_twitter

seoul-bike-rental-prediction---ai-pro---iti

The Seoul Metropolitan Government launched a public bike-sharing service in 2015 called Seoul Bikes (“Ddareungi” in Korean). It was designed to be a self-operating rental service that could be used conveniently by anyone. Today in Seoul, there are over 150 rental stations centered in five areas of the city (Yeouido, Sangam, Sinchon, the 4 Great Gates area, and Seongsu). Currently there are 2,000 Seoul Bikes available to users, with plans to expand the project in the coming years. Seoul Bikes are a great way to travel distances that are a bit too far to walk, but a bit to close to bother with public transportation or a taxi. The bikes are eco-friendly, user friendly, and low-cost. Take a bike out for a spin and see a new side of Seoul.