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$40 USD/oră
Steagul GEORGIA
batumi, georgia
$40 USD/oră
Momentan, aici e ora 4:31 a.m.
S-a înregistrat pe mai 22, 2020
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Pouya A.

@DeepLearningLab

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$40 USD/oră
Steagul GEORGIA
batumi, georgia
$40 USD/oră
Indisponibil
Proiecte finalizate
Indisponibil
Conform bugetului
Indisponibil
La timp
Indisponibil
Rata de angajare repetată

Software Engineer | Machine Learning | Robotics

Successful Software Engineer and Machine Learning with decades of verifiable success leading teams in delivering appropriate technology solutions for robotic systems, desktop, and mobile automation. Comprehensive knowledge of platform development, enterprise architecture, and agile methodologies. Innovative change agent with a unique mix of high-level technology direction and deep technical expertise. Skilled in Python, C#, Java, Deep Learning, Robotics, and Self-driving Cars.
Freelancer PHP Developers Georgia
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Portfoliu

6640472
In this repository, I am going to implement a Sentiment Analysis on the IMDB reviews by using RNN. So based on this project user can put his opinion for each movie he wants, then he will receive a suitable sentiment about it. One of the fantastic parts of this project would be deploying this project into a server as a Web Application. So a user can open a browser and puts his data and gets feedback.
Sentiment Analysis
In this repository, I am going to implement a Sentiment Analysis on the IMDB reviews by using RNN. So based on this project user can put his opinion for each movie he wants, then he will receive a suitable sentiment about it. One of the fantastic parts of this project would be deploying this project into a server as a Web Application. So a user can open a browser and puts his data and gets feedback.
Sentiment Analysis
6640469
In this repository, I am going to generate realistic looking faces with Machine Learning. In order to do so, we are going to leverage Generative Adversarial Networks (GANs), and more specifically Deep Convolutional Generative Adversarial Networks (DCGANs). By using this repository, you will be able to successfully train a GAN to sample an infinite amount of images based on a given dataset, which in our case will be human faces. https://github.com/PooyaAlamirpour/FaceGeneration
Face Generator
6640462
In this project, I'll generate Seinfeld TV scripts using RNNs. I'll be using a Seinfeld dataset of scripts from 9 seasons. The Neural Network I'll build will generate a new, "fake" TV script. For implementing this project we have some topics as below: Natural language processing (NLP) RNN (LSTM, GRU) Word embedding https://github.com/PooyaAlamirpour/TV-Script-Generation
TV Script Generation RNN
6640459
In this project, I have implemented a Dog Classification by using the Convolutional Neural Networks (CNN). This project can be used in a web or mobile app to process real-world, user-supplied images. Given an image of a dog, this algorithm will identify an estimate of the canine’s breed. If supplied with an image of a human, the code will identify the resembling dog breed.
Dog Classification
6640452
This project is an aspect of a big project that is called the Self-Driving Car. The self-driving car is a fantastic technology that needs lots of crucial skills. One of the essential techniques in Self-Driving Car engineering is detecting the Traffic Sign. For acquiring to being a specialist in Self-Driving Car, we should know about recognizing the traffic sign and other obstacles on the road. I have prepared a video when I was working on implementing this project. I can share it if you are interested. This project is implemented using the Python programming language.
Traffic Sign Classifier - Self-Driving Car
6640406
Path Planning - Self-Driving Car
6640472
In this repository, I am going to implement a Sentiment Analysis on the IMDB reviews by using RNN. So based on this project user can put his opinion for each movie he wants, then he will receive a suitable sentiment about it. One of the fantastic parts of this project would be deploying this project into a server as a Web Application. So a user can open a browser and puts his data and gets feedback.
Sentiment Analysis
In this repository, I am going to implement a Sentiment Analysis on the IMDB reviews by using RNN. So based on this project user can put his opinion for each movie he wants, then he will receive a suitable sentiment about it. One of the fantastic parts of this project would be deploying this project into a server as a Web Application. So a user can open a browser and puts his data and gets feedback.
Sentiment Analysis
6640469
In this repository, I am going to generate realistic looking faces with Machine Learning. In order to do so, we are going to leverage Generative Adversarial Networks (GANs), and more specifically Deep Convolutional Generative Adversarial Networks (DCGANs). By using this repository, you will be able to successfully train a GAN to sample an infinite amount of images based on a given dataset, which in our case will be human faces. https://github.com/PooyaAlamirpour/FaceGeneration
Face Generator
6640462
In this project, I'll generate Seinfeld TV scripts using RNNs. I'll be using a Seinfeld dataset of scripts from 9 seasons. The Neural Network I'll build will generate a new, "fake" TV script. For implementing this project we have some topics as below: Natural language processing (NLP) RNN (LSTM, GRU) Word embedding https://github.com/PooyaAlamirpour/TV-Script-Generation
TV Script Generation RNN
6640459
In this project, I have implemented a Dog Classification by using the Convolutional Neural Networks (CNN). This project can be used in a web or mobile app to process real-world, user-supplied images. Given an image of a dog, this algorithm will identify an estimate of the canine’s breed. If supplied with an image of a human, the code will identify the resembling dog breed.
Dog Classification
6640452
This project is an aspect of a big project that is called the Self-Driving Car. The self-driving car is a fantastic technology that needs lots of crucial skills. One of the essential techniques in Self-Driving Car engineering is detecting the Traffic Sign. For acquiring to being a specialist in Self-Driving Car, we should know about recognizing the traffic sign and other obstacles on the road. I have prepared a video when I was working on implementing this project. I can share it if you are interested. This project is implemented using the Python programming language.
Traffic Sign Classifier - Self-Driving Car
6640406
Path Planning - Self-Driving Car

Recenzii

Modificările au fost salvate
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Experiență

Full Stack Developer

Upworks
mai 2019 - Prezent
Working as a freelancer in Upwork gives chance to implement amazing projects. One of the amazing projects was implementing a desktop application for making a connection between source and destination PC. The fantastic part of this project for me was using Electron Framework for implementing remote desktop applications by using pure javascript. Some of the features I implemented for the projects were: Sharing screen, sharing mouse and keyboard, uploading files, chatting capability.

Senior .NET Software Developer, Full-Stack

Opus
sept. 2017 - sept. 2019 (2 ani)
Designing a robust platform name HealthNet which was supposed to be used by doctors for transferring patient documents. The product had to pass high-level security standards. To achieve the goal, I had to implement a new protocol using ebXML structure. The user could send and receive valuable data safely in a convenient structure. In the final phases, I collaborated with a big company named Opus, which is in charge of storing all related data for Norway citizens.

Senior .NET Software Developer, Full-Stack

Sarveen
nov. 2016 - dec. 2017 (1 an, 1 lună)
I have designed and implemented a scalable web-based smart application named SmartCattle which used various technologies for boosting the quality and quantity of production in dairy farms. The modular design allowed seamless upgrades as the farm requirements evolve. Smart Cattle records and analyses livestock activities and eating patterns for monitoring their health. All the features were presented in a friendly and easy to use frontend.

Calificări

Self-Driving Car

Udacity
2020
The Udacity Self-Driving Car is one of the best courses that I have ever experienced. Researchers will be experienced a real atmosphere class that can be an excellent opportunity for who want to gain substantial experience in this subjects such as Advanced Lane Lines Detection, Deep Learning approach of autonomous development, Traffic Sign Classifier, Computer Vision, Sensor Fusion, Kidnapped Vehicle, Localization, Robotics, and Path Planning. https://graduation.udacity.com/confirm/LCE44TAL

Deep Learning

Udacity
2019
The Deep Learning course is one of the wonderful lessons of Udacity which is in collaboration with Amazon. I have experienced some projects such as Auto-generation TV-Script, DeepFake face generation, and Sentiment Analysis of IMDB. This course gives me lots of powerful ideas for finding a solution to various problems. These fantastic four months is unforgettable for me. I have shared my implemented projects, feel free to use them. https://graduation.udacity.com/confirm/AC9MDAMA

Advanced C++

Udacity
2019
I have graduated from the C++ Udacity Nanodegree Program and had the chance to experience real projects based on OOP and how efficiently programming in memory use and lots of crucial techniques in multi-threading. I got hands-on experience by coding some real-world projects. Route planner using OpenStreetMap and A* Algorithm Processing monitor for the Linux Implementing awesome projects using smart pointers and multi-thread Building a C++ Chatbot https://graduation.udacity.com/confirm/C6N7PHD6

Publicații

Control Humanoid Robot using Intelligent Optimization Algorithms Fusion with Fourier

IEEE
Robot walking on two feet is a complex motion. Researchers are trying to improve biped robots walking. This article will introduce a new algorithm based on learning automata along with a continual action on control signals of humanoid robot's motion, showing the success of the proposed method as the result to be used for optimizing the parameters of TFS after being compared with the results of GA implementation. https://ieeexplore.ieee.org/document/8319381

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