FawziElNaggar

DashBord

Deep-Nural-Network-Tasks

Create ANN and CNN to train the model

Different-Machine-Learning-about-Actual-weather-dataset

Examples-of-Scrapping

Generate-Questions-and-Answering-using-NLP

Generate question with different types from any kind of text data and get answers for it.

ITI_Java_Tasks

Build machine learning models using java

londonrelocation_Scrapping

using Python and Scrapy framework in Rentola and thus we are providing the basic structure for your to utilize the same tools to scrap the website. Your goal is to be able to: Traverse the areas with their links listed in this page https://londonrelocation.com/properties-to-rent/ such as Fulham, Canary Wharf Angel, and etc. (Already Implemented by us as an example) Visit each area link and traverse the paginated properties lists (page 1 and page 2 only are sufficient). Do not hard code the pages links in step2, scrap them from the area page from step1. For each property you need to save the property title, price per month, and property URL.

Multi-text-Text-Classification

Build ML model based on Text classification to predict the industry based on job title column

Numerical_Optimization-Algorithms

Build from scratch different numerical optimization algorithms using python

Question-MCQ-_Answer_Generation

Building this project to generate MCQ Questions from any type of text and generate answers and distractors for it.

FawziElNaggar/Question-MCQ-_Answer_Generation

Building this project to generate MCQ Questions from any type of text and generate answers and distractors for it.

FawziElNaggar/londonrelocation_Scrapping

using Python and Scrapy framework in Rentola and thus we are providing the basic structure for your to utilize the same tools to scrap the website. Your goal is to be able to: Traverse the areas with their links listed in this page https://londonrelocation.com/properties-to-rent/ such as Fulham, Canary Wharf Angel, and etc. (Already Implemented by us as an example) Visit each area link and traverse the paginated properties lists (page 1 and page 2 only are sufficient). Do not hard code the pages links in step2, scrap them from the area page from step1. For each property you need to save the property title, price per month, and property URL.

FawziElNaggar/Multi-text-Text-Classification

Build ML model based on Text classification to predict the industry based on job title column

FawziElNaggar/DashBord

FawziElNaggar/Deep-Nural-Network-Tasks

Create ANN and CNN to train the model

FawziElNaggar/Different-Machine-Learning-about-Actual-weather-dataset

FawziElNaggar/Examples-of-Scrapping

FawziElNaggar/Generate-Questions-and-Answering-using-NLP

Generate question with different types from any kind of text data and get answers for it.

FawziElNaggar/ITI_Java_Tasks

Build machine learning models using java

FawziElNaggar/Numerical_Optimization-Algorithms

Build from scratch different numerical optimization algorithms using python

FawziElNaggar/Nural-Network-to-Context-Pneumonia-

FawziElNaggar/Power-BI-Dashboards

Power BI Dashboards

FawziElNaggar/Spark