Hosein1358

Pinned Repositories

linkedin-skill-assessments-quizzes
Full reference of LinkedIn answers 2023 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers
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XRP_ANALYSIS_2023
Here you can find analysis on the prices of XRP in 2023 plus the prediction of the prices for the first three months of 2024.
Language:Python11
Freelancer-Teaching-Platform
Language:HTML00
guess-word
Language:JavaScript2 1 00
linkedin-skill-assessments-quizzes
Full reference of LinkedIn answers 2022 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers
1 0 00
Neural-Network-Implementation
This Python code implements a simple neural network with one input layer, one hidden layer, and one output layer. The neural network is initialized with random weights and uses the sigmoid activation function. It is capable of both querying (forward pass) and training (backpropagation) processes.
Language:Jupyter Notebook10
Tennis_atp_2022
Language:Python00
XRP-Analysis
The analysis of XRP
Language:Jupyter Notebook20
XRP_ANALYSIS_2023
Here you can find analysis on the prices of XRP in 2023 plus the prediction of the prices for the first three months of 2024.
Language:Python10

Hosein1358's Repositories

Hosein1358/guess-word
Language:JavaScript2 1 00
Hosein1358/XRP-Analysis
The analysis of XRP
Language:Jupyter Notebook20
Hosein1358/linkedin-skill-assessments-quizzes
Full reference of LinkedIn answers 2022 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers
1 0 00
Hosein1358/Neural-Network-Implementation
This Python code implements a simple neural network with one input layer, one hidden layer, and one output layer. The neural network is initialized with random weights and uses the sigmoid activation function. It is capable of both querying (forward pass) and training (backpropagation) processes.
Language:Jupyter Notebook10
Hosein1358/XRP_ANALYSIS_2023
Here you can find analysis on the prices of XRP in 2023 plus the prediction of the prices for the first three months of 2024.
Language:Python10
Hosein1358/Freelancer-Teaching-Platform
Language:HTML00
Hosein1358/Tennis_atp_2022
Language:Python00