data collection for machine learning models
Dibayar semasa penghantaran
I am looking for a freelancer to assist with data collection for machine learning models. The ideal candidate should have experience in collecting text data from various sources.
- THIS PROJECT REQUIRES THAT YOU INDEPENDENTLY SOURCE REQUIRED DATASETS WITHOUT GIVEN SOURCES. PLEASE STATE IN YOUR PROPOSAL YOUR EXPERIENCE AND ABILITY IN SOURCING SUCH DATA.
Ideal Skills and Experience:
- Prior experience in data collection for machine learning models, specifically with text data.
- Familiarity with different sources for collecting text data.
- Strong attention to detail to ensure accurate and relevant data collection.
Please note that the collected data will be used solely for model training purposes.
main requirement: i need help sourcing datasets about people. It must be personal data sets from coutnries which have open privacy laws meaning this datasets can be used and are not bound by privacy laws. please see below the categories of personal data requried:
Identification Data: This includes names, Social Security numbers, passport numbers, driver's license numbers, and other similar data used primarily for identifying an individual.
Contact Data: Addresses (physical and email), phone numbers, and other similar information that allows someone to get in touch with an individual.
Demographic Data: This covers attributes such as age, gender, nationality, marital status, ethnicity, etc.
Financial Data: Account numbers, credit/debit card information, transaction details, credit history, and other financial information.
Technical Data: IP addresses, login data, cookies, and other online identifiers that might be used for online tracking or user identification.
Health Data: Medical histories, genetic data, biometric data, and any other data that pertains to an individual's physical or mental health.
Employment Data: Job titles, work history, educational background, professional qualifications, and other related data.
Behavioral Data: This includes purchase histories, web browsing histories, app usage, and other data related to an individual's behavior, preferences, and habits.
Location Data: Geographical location details which might be derived from devices or provided by users directly.
Social Data: Details from social networking sites, relationships, friend lists, interests, likes/dislikes, and other such information.
Opinions and Beliefs: Data related to an individual's religious, philosophical, and political beliefs, trade union membership, and other opinions.
Legal Data: Criminal records, disputes, litigations, and other legal-related information.
Special Categories of Personal Data: Under the General Data Protection Regulation (GDPR) in the European Union, there are special categories of personal data that require higher levels of protection. This includes data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, genetic data, biometric data, health data, and data concerning a person's sex life or sexual orientation.
When handling personal data, it's essential to consider the legal and ethical implications, especially when it comes to protecting an individual's privacy. Different jurisdictions have different regulations concerning the processing of personal data, so always ensure compliance with local laws and best practices.
ID Projek: #37252192
65 pekerja bebas membida secara purata $132 untuk pekerjaan ini
I am skilled Swift coder with skills including Research, Excel, Data Entry, Data Processing and Data Mining. Please contact me to discuss more about this project. Thank you