Comprehensive Machine Learning Application Development
Budget: $750 – $1,500 USD
I'm looking to develop a comprehensive machine learning application that encompasses predictive analytics, natural language processing (NLP), and image recognition. A particular focus will be on sentiment analysis within the NLP component.
Key Requirements:
- Proficiency in machine learning algorithms and techniques.
- Extensive experience in predictive analytics, image recognition and natural language processing.
- Specialized skills in sentiment analysis.
- Previous work in developing complex machine learning applications would be an advantage.
- Good understanding of app development principles.
Your task will be to create a machine-learning application that can:
- Analyze and predict trends based on data (predictive analytics).
- Understand and interpret human language and sentiment (NLP and sentiment analysis).
- Recognize and interpret visual data (image recognition).
NEED FREELANCER THAT UNDERSTANDS GOOGLE CLOUD VERTEX - AI MACHINE-LEARNING TECHNOLOGY.
THE GOOGLE CLOUD PLATFORM WILL BE PROVIDED TO THE FREELANCER
Please provide examples of your previous work in machine learning and app development.
SCOPE OF TASK
## SOP: Building Machine Learning Program for PHP Laravel Programme
### Objective:
To integrate Google Cloud Vertex AI Machine-learning technology for the PHP Laravel programme that can search for various components or items extracted from service provider database on the web to generate Images, Specifications and Assist in writing project description scope of works using refilled data provided by machine learning technology to provide approximate and detailed estimates.
### Key Steps:
1. Access the full representation of services.com admin section of the website.
2. Focus on the detailed estimation form for activities.
3. Click on a country, navigate to the activity category, and select a specific activity.
4. Machine learning should recognize the description of the activity and search for images, specifications, and prices on the internet.
5. Display the image and specification in the top box and prices in the bottom box on the detailed estimation form.
6. Write a full description of the component based on the selected activities.
7. Add multiple activities to the estimation form by loading each activity and arranging them in the order needed.
8. Once all activities are added, finalize the estimate.
### Cautionary Notes:
- Ensure that the machine learning program accurately recognizes and retrieves information related to the selected activities.
- Double-check the displayed images, specifications, and prices to ensure they match the selected activities.
- Be cautious when adding multiple activities to avoid errors in the estimation process.
### Tips for Efficiency:
- Streamline the process by systematically selecting and adding activities to the estimation form.
- Verify the accuracy of the information retrieved by the machine learning program before finalizing the estimate.
- Organize the activities in a logical order to facilitate a smooth estimation process.
Link to Loom
https://www.loom.com/share/a19890285f2c4d98bb813183d3b7a810
Key Requirements:
- Proficiency in machine learning algorithms and techniques.
- Extensive experience in predictive analytics, image recognition and natural language processing.
- Specialized skills in sentiment analysis.
- Previous work in developing complex machine learning applications would be an advantage.
- Good understanding of app development principles.
Your task will be to create a machine-learning application that can:
- Analyze and predict trends based on data (predictive analytics).
- Understand and interpret human language and sentiment (NLP and sentiment analysis).
- Recognize and interpret visual data (image recognition).
NEED FREELANCER THAT UNDERSTANDS GOOGLE CLOUD VERTEX - AI MACHINE-LEARNING TECHNOLOGY.
THE GOOGLE CLOUD PLATFORM WILL BE PROVIDED TO THE FREELANCER
Please provide examples of your previous work in machine learning and app development.
SCOPE OF TASK
## SOP: Building Machine Learning Program for PHP Laravel Programme
### Objective:
To integrate Google Cloud Vertex AI Machine-learning technology for the PHP Laravel programme that can search for various components or items extracted from service provider database on the web to generate Images, Specifications and Assist in writing project description scope of works using refilled data provided by machine learning technology to provide approximate and detailed estimates.
### Key Steps:
1. Access the full representation of services.com admin section of the website.
2. Focus on the detailed estimation form for activities.
3. Click on a country, navigate to the activity category, and select a specific activity.
4. Machine learning should recognize the description of the activity and search for images, specifications, and prices on the internet.
5. Display the image and specification in the top box and prices in the bottom box on the detailed estimation form.
6. Write a full description of the component based on the selected activities.
7. Add multiple activities to the estimation form by loading each activity and arranging them in the order needed.
8. Once all activities are added, finalize the estimate.
### Cautionary Notes:
- Ensure that the machine learning program accurately recognizes and retrieves information related to the selected activities.
- Double-check the displayed images, specifications, and prices to ensure they match the selected activities.
- Be cautious when adding multiple activities to avoid errors in the estimation process.
### Tips for Efficiency:
- Streamline the process by systematically selecting and adding activities to the estimation form.
- Verify the accuracy of the information retrieved by the machine learning program before finalizing the estimate.
- Organize the activities in a logical order to facilitate a smooth estimation process.
Link to Loom
https://www.loom.com/share/a19890285f2c4d98bb813183d3b7a810
Related categories:
Business, Accounting, Human Resources & Legal
Python
Algorithm
Machine Learning (ML)
Google APIs