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$15 USD / hour
Flag of IN
lucknow, india
$15 USD / hour
It's currently 5:43 AM here
Joined July 9, 2021
0 Recommendations

Shaily S.

@shailyshafeeque

monthly-level-four.svg
5.0 (3 reviews)
2.7
2.7
$15 USD / hour
Flag of IN
lucknow, india
$15 USD / hour
100%
Jobs Completed
100%
On Budget
100%
On Time
N/A
Repeat Hire Rate

TOP 2% FREELANCER |Web I Mobile App I CRM I ERP

Hello, We are a Web, and application development company. We deliver excellence for all type of business and every solution provided by us is unique and innovative. Client satisfaction is our first priority! My expertise: 1. PHP, Laravel, Cake php, Codeigniter. 2. HTML/CSS, Bootstrap, HTML 3. Magento, opencart, Drupal, Shopify and WordPress CMS. 4.jQuery, Ajax 5. Angular,Node, view, react native 6. Mobile app with ionic/cordova, react, Swift / Objective-c 7. Unity 3d game / Html5, pixi js/2d game We will deliver the result in a timely manner and earn your trust. we have worked with clients all across the globe and I would love to work with you as well. Thanks!
Freelancer Android Developers India

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Portfolio Items

Steps Taken

All images are cropped and resized using the resize script and pre-processing script.
Images without disease were projected using the rotation script; Images with disease were reflected and rotated 90, 120, 180 and 270 degrees.
After rotating and reflecting with and without disease, the class imbalance has been resolved and detected several thousand images have disease.
In total, there are 5000 images processed by the neural network.
All images were converted to NumPy Arrays using the conversion script. NumPy Arrays combined images and tags in an array and send the images to CNN.
The model was created by using the TensorFlow and Keras libraries. For CNN, encoding was done by using anaconda as IDE and Jupyter Notepad within anaconda.
The pictures are tagged and parsed the pictures used to train them in two different sequences according to the labelling.
The pictures were then brought to a fixed size (255*255) by grayscale method .
The images are then passed through CNN and
Flutter TensorFlow Lite Artificial Intelligence Application
Steps Taken

All images are cropped and resized using the resize script and pre-processing script.
Images without disease were projected using the rotation script; Images with disease were reflected and rotated 90, 120, 180 and 270 degrees.
After rotating and reflecting with and without disease, the class imbalance has been resolved and detected several thousand images have disease.
In total, there are 5000 images processed by the neural network.
All images were converted to NumPy Arrays using the conversion script. NumPy Arrays combined images and tags in an array and send the images to CNN.
The model was created by using the TensorFlow and Keras libraries. For CNN, encoding was done by using anaconda as IDE and Jupyter Notepad within anaconda.
The pictures are tagged and parsed the pictures used to train them in two different sequences according to the labelling.
The pictures were then brought to a fixed size (255*255) by grayscale method .
The images are then passed through CNN and
Flutter TensorFlow Lite Artificial Intelligence Application
Steps Taken

All images are cropped and resized using the resize script and pre-processing script.
Images without disease were projected using the rotation script; Images with disease were reflected and rotated 90, 120, 180 and 270 degrees.
After rotating and reflecting with and without disease, the class imbalance has been resolved and detected several thousand images have disease.
In total, there are 5000 images processed by the neural network.
All images were converted to NumPy Arrays using the conversion script. NumPy Arrays combined images and tags in an array and send the images to CNN.
The model was created by using the TensorFlow and Keras libraries. For CNN, encoding was done by using anaconda as IDE and Jupyter Notepad within anaconda.
The pictures are tagged and parsed the pictures used to train them in two different sequences according to the labelling.
The pictures were then brought to a fixed size (255*255) by grayscale method .
The images are then passed through CNN and
Flutter TensorFlow Lite Artificial Intelligence Application
Steps Taken

All images are cropped and resized using the resize script and pre-processing script.
Images without disease were projected using the rotation script; Images with disease were reflected and rotated 90, 120, 180 and 270 degrees.
After rotating and reflecting with and without disease, the class imbalance has been resolved and detected several thousand images have disease.
In total, there are 5000 images processed by the neural network.
All images were converted to NumPy Arrays using the conversion script. NumPy Arrays combined images and tags in an array and send the images to CNN.
The model was created by using the TensorFlow and Keras libraries. For CNN, encoding was done by using anaconda as IDE and Jupyter Notepad within anaconda.
The pictures are tagged and parsed the pictures used to train them in two different sequences according to the labelling.
The pictures were then brought to a fixed size (255*255) by grayscale method .
The images are then passed through CNN and
Flutter TensorFlow Lite Artificial Intelligence Application
Steps Taken

All images are cropped and resized using the resize script and pre-processing script.
Images without disease were projected using the rotation script; Images with disease were reflected and rotated 90, 120, 180 and 270 degrees.
After rotating and reflecting with and without disease, the class imbalance has been resolved and detected several thousand images have disease.
In total, there are 5000 images processed by the neural network.
All images were converted to NumPy Arrays using the conversion script. NumPy Arrays combined images and tags in an array and send the images to CNN.
The model was created by using the TensorFlow and Keras libraries. For CNN, encoding was done by using anaconda as IDE and Jupyter Notepad within anaconda.
The pictures are tagged and parsed the pictures used to train them in two different sequences according to the labelling.
The pictures were then brought to a fixed size (255*255) by grayscale method .
The images are then passed through CNN and
Flutter TensorFlow Lite Artificial Intelligence Application
Ecommerce flutter application
ecoomerce flutter application
Barcode software, best pos, best retail pos, gst, inventory management software, Invoicing Software, point of sale, Point Of Sale Software, pos, pos software, Retail POS, retail shop software, shop management software
POS Stock management
Barcode software, best pos, best retail pos, gst, inventory management software, Invoicing Software, point of sale, Point Of Sale Software, pos, pos software, Retail POS, retail shop software, shop management software
POS Stock management
Barcode software, best pos, best retail pos, gst, inventory management software, Invoicing Software, point of sale, Point Of Sale Software, pos, pos software, Retail POS, retail shop software, shop management software
POS Stock management
Barcode software, best pos, best retail pos, gst, inventory management software, Invoicing Software, point of sale, Point Of Sale Software, pos, pos software, Retail POS, retail shop software, shop management software
POS Stock management
Barcode software, best pos, best retail pos, gst, inventory management software, Invoicing Software, point of sale, Point Of Sale Software, pos, pos software, Retail POS, retail shop software, shop management software
POS Stock management
Barcode software, best pos, best retail pos, gst, inventory management software, Invoicing Software, point of sale, Point Of Sale Software, pos, pos software, Retail POS, retail shop software, shop management software
POS Stock management
Barcode software, best pos, best retail pos, gst, inventory management software, Invoicing Software, point of sale, Point Of Sale Software, pos, pos software, Retail POS, retail shop software, shop management software
POS Stock management
Barcode software, best pos, best retail pos, gst, inventory management software, Invoicing Software, point of sale, Point Of Sale Software, pos, pos software, Retail POS, retail shop software, shop management software
POS Stock management
Perfect restaurant management system
Restaurent management system
Perfect restaurant management system
Restaurent management system
Perfect restaurant management system
Restaurent management system
Perfect restaurant management system
Restaurent management system
Dashboard
 Departments
 Doctor
 Patient
 Schedule
 Appointment
 Human Resources
 Financial Activities
 Prescription
 Lab Tests
 Medicine
 Pharmacy
 Donor
Blood Bank
 Bed
 Report
 Notice
 Email
 SMS
 Website
 Settings
 Profile
Hospital management system
Dashboard
 Departments
 Doctor
 Patient
 Schedule
 Appointment
 Human Resources
 Financial Activities
 Prescription
 Lab Tests
 Medicine
 Pharmacy
 Donor
Blood Bank
 Bed
 Report
 Notice
 Email
 SMS
 Website
 Settings
 Profile
Hospital management system
Dashboard
 Departments
 Doctor
 Patient
 Schedule
 Appointment
 Human Resources
 Financial Activities
 Prescription
 Lab Tests
 Medicine
 Pharmacy
 Donor
Blood Bank
 Bed
 Report
 Notice
 Email
 SMS
 Website
 Settings
 Profile
Hospital management system
Dashboard
 Departments
 Doctor
 Patient
 Schedule
 Appointment
 Human Resources
 Financial Activities
 Prescription
 Lab Tests
 Medicine
 Pharmacy
 Donor
Blood Bank
 Bed
 Report
 Notice
 Email
 SMS
 Website
 Settings
 Profile
Hospital management system
Dashboard
 Departments
 Doctor
 Patient
 Schedule
 Appointment
 Human Resources
 Financial Activities
 Prescription
 Lab Tests
 Medicine
 Pharmacy
 Donor
Blood Bank
 Bed
 Report
 Notice
 Email
 SMS
 Website
 Settings
 Profile
Hospital management system
Dashboard
 Departments
 Doctor
 Patient
 Schedule
 Appointment
 Human Resources
 Financial Activities
 Prescription
 Lab Tests
 Medicine
 Pharmacy
 Donor
Blood Bank
 Bed
 Report
 Notice
 Email
 SMS
 Website
 Settings
 Profile
Hospital management system

Reviews

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Showing 1 - 3 out of 3 reviews
Filter reviews by:
5.0
$55.00 USD
Nice to work with Shaily with issue meeting reports
Java Android Kotlin
User Avatar
Flag of NG Adike K. @kizinho
13 days ago
5.0
₹600.00 INR
Nice to work with. Nice Professionalism.
Flutter
User Avatar
Flag of IN Siddhartha C. @sch59b634f36c24e
28 days ago
5.0
$150.00 USD
A wonderful job. Our app was made in record time. Thank you
PHP Mobile App Development iPhone Android C# Programming
User Avatar
Flag of AL Francesko L. @franeskolame
28 days ago

Publications

Area Of Expertise:

Shailly
Having rich experince in CORE PHP ,CODEIGNITER,LARAVEL and ORM QUERY Builder. Currently we're working on CI4 and Laravel 8.X.we also know JS frameworks like Vue.JS, React. we're expert in ANDROID application development, build more than 50+ application in native with android studio. Also we've experince in cross platforms like React Native and Flutter.

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Top Skills

Android 2 PHP 1 Java 1 Kotlin 1 Flutter 1

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