Logo Freelancer
Log Masuk Daftar
Siarkan Projek
MENJELAJAH
Amazon Web Services
Computer Vision
Machine Learning (ML)
Programming
Python
Gambar muka depan profil
Anda kini mengikuti
Ralat mengikuti pengguna.
Pengguna ini tidak membenarkan pengguna untuk mengikuti mereka.
Anda telah mengikuti pengguna ini.
Pelan keahlian anda hanya membenarkan 0 mengikuti. Naik taraf di sini.
Berjaya menyahikut
Ralat tidak mengikuti pengguna.
Anda berjaya mengesyorkan
Ralat mengesyorkan pengguna.
Sesuatu telah berlaku. Sila segar semula halaman dan cuba lagi.
E-mel berjaya disahkan.
Avatar Pengguna

Ahmad Wafri C.

@ahmadwafri

verified-v2.svg
5.0
7
3.6
3.6
57%

Top AI & Full-Stack

$30 USD / Jam
・
Bendera
Malaysia (4:53 PTG)
・
Menyertai pada Jun 7, 2023
$30 USD / Jam
・
I'm working on AI technologies and web development such like NLP, ASR, CV, full stack and so on for long years. I've expertized to several AI model building/deploying with extensible, scalable functionalities. Top skills are ChatBot, NER, RE, QA and Stock AI, Speech Analysis, Computer Vision AI, full stack. For 13 years Iive spent programming (8 as primary income) Iive been cultivating persistence, performance, and a love for challenges, which allows me to consistently deliver complex tasks that others might give up. Of course, programming is always a learning experience and I am to this day doing that.
Pengesahan
Tepat pada masa
100%
Mengikut bajet
100%
Kadar terima
70%
Freelancer Python Developers Malaysia
Lihat semua Python Developers dalam Malaysia

Portfolio

Portfolio

12028006
In this notebook, I built and train a Multi-Step / Multi-Output Regression Model powered by TensorFlow & Keras in order to predict Bitcoin's future trend. Even though a hyperparameter tuning mechanism is out of the scope of this notebook, I have tried a series of networks such as: Dense, Convolutional with and without Max Pooling, Long Short-Term Memory (LSTM), Gated Recurrent Unit, etc. The metrics I was using to evaluate how well our model generalizes when predicting on unseen data are MAE (Mean Absolute Error) and MSE (Mean Squared Error). The Neural Network that scores the lowest loss is the one that should be deployed to production. It is also important to mention that this model will be trained based on the moving averages as the Bitcoin's price is full of noise, and I don't want our model to learn useless patterns
Cryptocurrency price prediction using LSTMs
In this notebook, I built and train a Multi-Step / Multi-Output Regression Model powered by TensorFlow & Keras in order to predict Bitcoin's future trend. Even though a hyperparameter tuning mechanism is out of the scope of this notebook, I have tried a series of networks such as: Dense, Convolutional with and without Max Pooling, Long Short-Term Memory (LSTM), Gated Recurrent Unit, etc. The metrics I was using to evaluate how well our model generalizes when predicting on unseen data are MAE (Mean Absolute Error) and MSE (Mean Squared Error). The Neural Network that scores the lowest loss is the one that should be deployed to production. It is also important to mention that this model will be trained based on the moving averages as the Bitcoin's price is full of noise, and I don't want our model to learn useless patterns
Cryptocurrency price prediction using LSTMs
In this notebook, I built and train a Multi-Step / Multi-Output Regression Model powered by TensorFlow & Keras in order to predict Bitcoin's future trend. Even though a hyperparameter tuning mechanism is out of the scope of this notebook, I have tried a series of networks such as: Dense, Convolutional with and without Max Pooling, Long Short-Term Memory (LSTM), Gated Recurrent Unit, etc. The metrics I was using to evaluate how well our model generalizes when predicting on unseen data are MAE (Mean Absolute Error) and MSE (Mean Squared Error). The Neural Network that scores the lowest loss is the one that should be deployed to production. It is also important to mention that this model will be trained based on the moving averages as the Bitcoin's price is full of noise, and I don't want our model to learn useless patterns
Cryptocurrency price prediction using LSTMs
In this notebook, I built and train a Multi-Step / Multi-Output Regression Model powered by TensorFlow & Keras in order to predict Bitcoin's future trend. Even though a hyperparameter tuning mechanism is out of the scope of this notebook, I have tried a series of networks such as: Dense, Convolutional with and without Max Pooling, Long Short-Term Memory (LSTM), Gated Recurrent Unit, etc. The metrics I was using to evaluate how well our model generalizes when predicting on unseen data are MAE (Mean Absolute Error) and MSE (Mean Squared Error). The Neural Network that scores the lowest loss is the one that should be deployed to production. It is also important to mention that this model will be trained based on the moving averages as the Bitcoin's price is full of noise, and I don't want our model to learn useless patterns
Cryptocurrency price prediction using LSTMs
11156463
- Utilize several cloud API for STT (Azure, AWS, GCP, SpeechBrain, etc) - Custom service based on trained model.
Speech to Text service
11156454
Chatbot can read various document type and answer to the question based on understanding from document content. It is capable to read docx, pdf, csv and webpage as of now.
Document readable Chatbot development
11156448
The service running on AWS will be high scalable, extendable, efficient by following this pipeline.
AWS service architecture
12028006
In this notebook, I built and train a Multi-Step / Multi-Output Regression Model powered by TensorFlow & Keras in order to predict Bitcoin's future trend. Even though a hyperparameter tuning mechanism is out of the scope of this notebook, I have tried a series of networks such as: Dense, Convolutional with and without Max Pooling, Long Short-Term Memory (LSTM), Gated Recurrent Unit, etc. The metrics I was using to evaluate how well our model generalizes when predicting on unseen data are MAE (Mean Absolute Error) and MSE (Mean Squared Error). The Neural Network that scores the lowest loss is the one that should be deployed to production. It is also important to mention that this model will be trained based on the moving averages as the Bitcoin's price is full of noise, and I don't want our model to learn useless patterns
Cryptocurrency price prediction using LSTMs
In this notebook, I built and train a Multi-Step / Multi-Output Regression Model powered by TensorFlow & Keras in order to predict Bitcoin's future trend. Even though a hyperparameter tuning mechanism is out of the scope of this notebook, I have tried a series of networks such as: Dense, Convolutional with and without Max Pooling, Long Short-Term Memory (LSTM), Gated Recurrent Unit, etc. The metrics I was using to evaluate how well our model generalizes when predicting on unseen data are MAE (Mean Absolute Error) and MSE (Mean Squared Error). The Neural Network that scores the lowest loss is the one that should be deployed to production. It is also important to mention that this model will be trained based on the moving averages as the Bitcoin's price is full of noise, and I don't want our model to learn useless patterns
Cryptocurrency price prediction using LSTMs
In this notebook, I built and train a Multi-Step / Multi-Output Regression Model powered by TensorFlow & Keras in order to predict Bitcoin's future trend. Even though a hyperparameter tuning mechanism is out of the scope of this notebook, I have tried a series of networks such as: Dense, Convolutional with and without Max Pooling, Long Short-Term Memory (LSTM), Gated Recurrent Unit, etc. The metrics I was using to evaluate how well our model generalizes when predicting on unseen data are MAE (Mean Absolute Error) and MSE (Mean Squared Error). The Neural Network that scores the lowest loss is the one that should be deployed to production. It is also important to mention that this model will be trained based on the moving averages as the Bitcoin's price is full of noise, and I don't want our model to learn useless patterns
Cryptocurrency price prediction using LSTMs
In this notebook, I built and train a Multi-Step / Multi-Output Regression Model powered by TensorFlow & Keras in order to predict Bitcoin's future trend. Even though a hyperparameter tuning mechanism is out of the scope of this notebook, I have tried a series of networks such as: Dense, Convolutional with and without Max Pooling, Long Short-Term Memory (LSTM), Gated Recurrent Unit, etc. The metrics I was using to evaluate how well our model generalizes when predicting on unseen data are MAE (Mean Absolute Error) and MSE (Mean Squared Error). The Neural Network that scores the lowest loss is the one that should be deployed to production. It is also important to mention that this model will be trained based on the moving averages as the Bitcoin's price is full of noise, and I don't want our model to learn useless patterns
Cryptocurrency price prediction using LSTMs
11156463
- Utilize several cloud API for STT (Azure, AWS, GCP, SpeechBrain, etc) - Custom service based on trained model.
Speech to Text service
11156454
Chatbot can read various document type and answer to the question based on understanding from document content. It is capable to read docx, pdf, csv and webpage as of now.
Document readable Chatbot development
11156448
The service running on AWS will be high scalable, extendable, efficient by following this pipeline.
AWS service architecture
Perubahan disimpan
5.0 · 7 Reviews
Ulasan
M
تطوير موقع تجارة شحن الألعاب والتطبيقات • $100 USD
لا يستطيع العمل الا بارسال الاموال اليه مقدما حقا اظن انه محتا
Mohamed A.
@mohameda193
•
Bendera
Minya, Egypt
•
6 bulan yang lalu
Kongsi
Avatar Pengguna
Bootstrap Website Content & Design Expert • $30 USD
Worst freelancer ever! wasted me a week of time, he cannot do anything! probably just take the project and give to another freelancer to do, it's just a simple html page, and replace some contents in it, he cannot complete and deliver the work, keep letting me wait, I should aware that's a negative sign, dont trust this guy, he will literally waste all your time until deadline, avoid!!!
Tom T.
@saasprivacy
•
Bendera
Central, Hong Kong
•
6 bulan yang lalu
Kongsi
Avatar Pengguna
Image Score Derivation and Selection Tool • $50 SGD
Ahmad has completed the project within timeline and met the requirements, his skill set on Python is extremely good.
Abdul Raheem G.
@etlfreelancer
•
Bendera
singapore, Singapore
•
7 bulan yang lalu
Kongsi
D
first topic • $50 USD
The project is not completed according to the dispute
Diane A.
@Diane40
•
Bendera
Oak Point, United States
•
7 bulan yang lalu
Kongsi
S
Create a specific Digit Recognition to detect date and time • ₹26,000 INR
He is good and have knowledge about the work and technologies he is working. He helped me with image processing, Open CV for time detection task in the image.
Sukumar Reddy M.
@sukumarreddy6
•
Bendera
Anantapur, India
•
2 tahun yang lalu
Kongsi
Jemputan berjaya dihantar!
Terima kasih! Kami telah menghantar pautan melalui e-mel kepada anda untuk menuntut kredit percuma anda.
Sesuatu telah berlaku semasa menghantar e-mel anda. Sila cuba lagi.
Logo Freelancer Malaysia / Bahasa Malaysia
Bantuan & Sokongan

Pekerja bebas

Kategori ProjekPeraduanPekerja BebasEnterprise Cabaran Inovasi Pembangunan AIKeahlianProgram Pekerja Bebas PilihanPengurusan ProjekPekerjaan TempatanPhoto AnywherePameranAPI untuk PembangunDisahkanAplikasi Desktop

Tentang

Tentang kamiBagaimana ia BerfungsiKeselamatanPelaburPeta LamanKisahDalam BeritaPasukanAnugerahSiaran AkhbarKerjaya

Terma

Dasar PrivasiTerma dan SyaratDasar HakciptaTatakelakuanYuran dan Caj

Rakan Kongsi

Escrow.comLoadshiftWarrior Forum

Aplikasi

Logo Apple App StoreLogo Mainan Google
Salin ke papan keratan gagal, sila cuba lagi selepas melaraskan kebenaran anda.
Disalin ke papan keratan.

Pengguna Berdaftar

Jumlah Pekerjaan Disiarkan

Freelancer ® is a registered Trademark of Freelancer Technology Pty Limited (ACN 142 189 759)

Copyright © 2025 Freelancer Technology Pty Limited (ACN 142 189 759)

Memuatkan pratonton
Kebenaran diberikan untuk Geolocation.
Sesi log masuk anda telah luput dan telah dilog keluar. Sila log masuk sekali lagi.