Website Design London Projects
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Google keywords search email data collection
Background: Company website: www.zhongjuntech.net. I want to hire a freelancer to do the data collection via Google search keywords to find sales agents and trading companies in 9 different countries, including Mexico, Russia, brazil, south Africa, Australia, India, Indonesia, Turkey, and Chile. use keywords below and add country after keywords.To clarify, I need email data for all those keywords and apply it to nine countries. There are at least 50 email addresses for each word for each country. trading companies, and B2B platforms for selling your rubber processing solutions, electrical solutions, and rubber injection molding machines in various countries: International sales agents for rubber machinery Rubber processing machinery sales representatives Industrial equipment sales agent network Global trading companies for industrial machinery Rubber processing equipment distributors Importers of rubber machinery B2B marketplace for rubber processing equipment Industrial machinery trade platforms Online B2B portals for manufacturing equipment International agents for industrial solutions Sales representatives for electrical solutions Agents for rubber technology equipment Global distributors for rubber machinery Industrial solutions trading partners Importers of electrical and rubber equipment B2B marketplace for electrical industrial solutions Online trade platform for rubber technology Industrial equipment B2B e-commerce sites Geographical Modifiers: Asian distributors for rubber processing machines North American B2B platforms for industrial machinery European trading companies for electrical solutions Rubber Processing Machinery & Solutions: Custom rubber processing machinery exporters Advanced rubber mixing systems distributors High-precision rubber extrusion equipment Rubber molding machine international dealers Automated rubber curing solutions Electrical Solutions for Industrial Automation: Industrial automation electrical components suppliers Electrical control systems for manufacturing agents High-efficiency electrical solutions for rubber production Custom electrical engineering solutions for industrial processes Rubber Injection Molding Machines: Precision rubber injection molding machine exporters High-performance rubber injection systems Vertical rubber injection molding equipment distributors Rubber injection machine sales representatives For Targeting Specific Markets or Needs: Energy-efficient rubber processing machinery in Asia Automated rubber production solutions for European market North American suppliers of industrial electrical solutions Customizable rubber machinery for South American manufacturers B2B industrial machinery trading platforms Global trade portals for rubber and electrical manufacturing equipment Online marketplaces for rubber processing technology Industrial solutions trading companies specializing in rubber and electrical Advanced Rubber Processing Technologies: High-tech rubber compounding solutions Rubber calendering equipment international suppliers Precision rubber cutting technology distributors Rubber recycling equipment for global market Specialized Electrical Solutions: Customized PLC systems for rubber manufacturing Electrical retrofitting services for rubber plants Energy-saving electrical systems for rubber production Industrial IoT solutions for rubber processing Rubber Injection Molding Innovations: Smart rubber injection molding solutions Silicone rubber injection equipment suppliers Thermoplastic rubber processing machinery Automated rubber molding systems with AI Silicone rubber extrusion equipment for North America High-speed rubber manufacturing machinery in Asia Rubber laboratory equipment for R&D centers worldwide International B2B platform for silicone rubber machinery Trade leads for rubber processing automation B2B networking for rubber machinery manufacturers Online expo for rubber and electrical industrial solutions Global agents for rubber processing innovations Distributors wanted for high-precision rubber machinery Sales agents specializing in industrial electrical systems Partnership opportunities for rubber machinery trading Mining companies in Russia: "mining companies Russia" Rubber manufacturers in South Africa: "rubber manufacturers South Africa" Electrical equipment suppliers in Brazil: "electrical equipment suppliers Brazil" Mining solutions in Chile: "mining solutions Chile" Rubber products manufacturers in India: "rubber products manufacturers India" Power industry companies in Mexico: "power industry companies Mexico" Rubber injection molding machines in Indonesia: "rubber injection molding machines Indonesia" Mining Equipment Distributors in Russia: "mining equipment distributors Russia" Industrial Rubber Suppliers in South Africa: "industrial rubber suppliers South Africa"
19 days ago33 proposalsRemoteopportunity
Automated Semantic Text Analysis Pipeline
Comprehensive Use Case Specification: Automated Semantic Text Analysis Pipeline Objective Develop an automated semantic text analysis pipeline that processes and analyses textual data extracted from documents. This pipeline enriches text with metadata for deeper insights and enables semantic search capabilities through a user-friendly interface. This stage of the project is for a MVP system should leverage AWS services such as Textract for text extraction, a text categorising stage with a simple to use GUI, all-mpnet-base-v2 for embedding, and Postgres with a vector extension. This job posting is for the MPV stage only, but we must be mindful of the stage two development and facilitate rapid and straightforward scalability in any stage one MPV processes. System Overview The solution encompasses AWS services for storage and processing, a custom interface for metadata enrichment, all-mpnet-base-v2 for generating text embeddings, Postgres and a vector extension for efficient storage and retrieval of vectors, and a custom-built web interface for user interaction. RAG will be implemented with a broad a context as possible to the model across a large document set. Phase 1: MVP Stage 1. Document Storage and Processing Trigger - Tool: Amazon S3. - Process: Upload documents (PDFs initially) to designated S3 buckets, documents will be remained in accordance with a set naming convention and key metadata relating to the document entered into the database for future reference. This triggers the subsequent text extraction process. For test purposes the uploads will be made manually, and at later stages a web scraper will be added that automatically places PDF documents into relevant S3 buckets. 2. Text Extraction - Tool: AWS Textract. - Process: Text is extracted from uploaded PDF documents and temporarily stored in A3 buckets to facilitate further processing. 3. Text Enrichment Developer to advise on best method of adding labels / categories to the text, via an easy to use interface. Labels to be added at a granular level to allow the return of text snippets, providing context to the LLM in formulating it's responses from a broad range of documents without exceeding the token limit. 4. Text Vectorization - Embedding tool: all-mpnet-base-v2 - LLM: Amazon SageMaker (using LLaMA 2). - Process: The text is processed with LLaMA 2 to generate vector embeddings, capturing semantic information for advanced analysis and search functionalities. 5. Vector Storage - Tool: Postgres with a vector extension - Process: Text vectors are stored in the database, allowing for efficient management and retrieval of vectorized data for semantic searches. 6. Front-end Web Application and Search Functionality - Front-end Technology: React.js. - Key Features: - Semantic search input and results display. - email input field for collecting contact information for marketing purposes, forwarding to the client's email address. - Homepage containing descriptive marketing text. - 3 pages total: home page, interaction page, contact page, plus a pop up with GDPR info. Graphics provided as template guidance. - Back-end Technology: Python with FastAPI. Phase 2: Full Automation and Scaling 1. Automated Document Ingestion - Process: A web scraping tool is implemented to automatically identify and upload new documents to the S3 bucket, facilitating a continuous flow of data into the pipeline without manual intervention. 2. Scalable Architecture - Deployment: The application components are containerized using Docker and managed with Kubernetes (Amazon EKS), ensuring the system can scale efficiently to accommodate increased data volumes and user queries. 3. Enhanced Processing Capabilities - Improvements: Integrate additional NLP and ML models for broader and more nuanced text analysis. Consider fine-tuning custom models for specific domain applications. 4. User registration and user management system integration. Please note the attached contract agreement that will be deemed agreed to upon acceptance of the project. Your price given on PPH will be deemed to be your full and final price, and you will be deemed to have fully understood the scope, brief, and specification. To provide context, the project business plan has been uploaded. This is for context only and does not form part of the brief.
21 days ago11 proposalsRemoteopportunity
Local Council Chatbot utilising Llama2 and dataset of PDF docs.
Full stack developer with relevant experience in AWS services and LLM deployment. Description Develop an MVP that provides a chat interface allowing users to query a dataset of local council documents, which will variously include minutes and policy documents. A dataset that contains all information relating to the purpose, policies, news, information, and decision making by that council. The dataset would contain approximately 100 PDF documents, and the chatbot would return meaningful and coherent answers to user prompts, while providing reference links to documents that information in the response is taken from. The client acknowledges the current limitations of LLMs in returning responses from queries across multiple documents, especially given current token limits and processing cost restrictions. A developer is sought that can leverage techniques to embed metadata in the text, allowing techniques such as RAG to extract snippets of data from multiple documents relating to the query and collate them into a response to the user, while adhering to token limits. Objective Develop an automated semantic text analysis pipeline that processes and analyses textual data extracted from documents using Llama2. This pipeline enriches text with metadata for deeper insights and enables semantic search capabilities through a user-friendly interface. This stage of the project is for a MVP system, leveraging AWS services such as Textract for text extraction, a text categorising stage with a simple to use GUI, all-mpnet-base-v2 for embedding, and Postgres with a vector extension. This job posting is for the MPV stage only, but we must be mindful of the stage two development and facilitate rapid and straightforward scalability in any stage one MPV processes. System Overview The solution encompasses AWS services for storage and processing, a custom interface for metadata enrichment, all-mpnet-base-v2 for generating text embeddings, Postgres and a vector extension for efficient storage and retrieval of vectors, and a custom-built web interface for user interaction. RAG will be implemented with a broad a context as possible to the model across a large document set. Phase 1: MVP Stage 1. Document Storage and Processing Trigger Tool: Amazon S3. Process: Upload documents (PDFs initially) to designated S3 buckets, documents will be renamed in accordance with a set naming convention and details of the document entered into the database. This triggers the subsequent text extraction process. For test purposes the uploads will be made manually, and at later stages a web scraper will be added that automatically places PDF documents into relevant S3 buckets. 2. Text Extraction - Tool: AWS Textract. - Process: Text is extracted from uploaded PDF documents and temporarily stored in A3 buckets to facilitate further processing. 3. Text Enrichment Developer to advise on best method of adding labels / categories to the text, via an easy to use interface. Labels to be added at a granular level to allow the return of text snippets from within the chunks of data, but with relevant metadata. The purpose of this is to provide context to the LLM in formulating responses from a broad range of documents without exceeding the token limit. 4. Text Vectorization • Embedding tool: all-mpnet-base-v2 • LLM: Amazon SageMaker (using LLaMA 2). Process: The text is processed with LLaMA 2 to generate vector embeddings, capturing semantic information for advanced analysis and search functionalities. 5. Vector Storage Tool: Postgres with a vector extension Process: Text vectors are stored in the database, allowing for efficient management and retrieval of vectorized data for semantic searches. 6. Front-end Web Application and Search Functionality Front-end Technology: • React.js. Key Features: • Semantic search input and results display. • email input field for collecting contact information for marketing purposes, forwarding to the client's email address. • Homepage containing descriptive marketing text. 3 pages total: home page, interaction page, contact page, plus a pop up with GDPR info. Graphics provided as template guidance. Back-end Technology: • Python with FastAPI. 7. Fine Tuning Allow for fine tuning based on a series of questions and responses to be provided by the client, until such point that coherent responses to queries are achieved. Phase 2: Full Automation and Scaling Beyond the scope of this job. Notes: The developer is to provide guidance and feedback on the capabilities of the technologies and is free to provide their own guidance and suggestions. However, the functionality of the system in providing coherent responses based on text snippets drawn from a large dataset is both the challenge and the absolute requirement. Please only bid with your full and final price. Placeholders will not be accepted. Completion with approximately two weeks. Please respond by explaining how you would handle the text enrichment?
21 days ago17 proposalsRemoteNeed people who used different hostings to write real reviews
We are looking for people who used and tested different hosting services provided by various companies on their real experience and wish to write reviews on https://hostings.info/ (payment guaranteed). The reviews should be written in English. They should be short but informative: contain information regarding the hosting service pros and cons, its pricing and quality, e.g. website performance speed, customer support level, reliability. In order to leave a review on our portal, you need to login via LinkedIn or Facebook.
a year ago244 proposalsRemoteIncrease organic reach to my website https://maidenventures.co/
Hi, We are looking for help with three specific tasks increase traffic to www.maidenventures.co design update a general website optimisation to increase the speed When anyone in Sydney type the following words I would like the website to come up Technology in construction Energy saving Solar loans Building energy audits Electricity savings Gas Savings Utility bills
3 years ago45 proposalsRemoteopportunity
Pattern maker and seamstress for athleisure wear
I am looking for a pattern maker who can create a sweatshirt pattern (I've got some rough ideas of having a slightly more curved and oversized sleeve), as well as a seamstress who can sew together the pattern pieces once they have been printed and dyed. (If you are both a pattern cutter and seamstress that would be amazing.) I need the final sweatshirts (5 in total) to be of high quality as I will be showing them at my postgrad degree show, my website and possibly to an independent boutique. Looking for a quick turnaround for both patterning and sewing. Many thanks Funmi
3 years ago28 proposalsRemoteCopywriting for Borowski Art Glass 文案 - 博罗夫斯基艺术玻璃
Borowski is a glass art brand that originated in Germany. Borowski passes its fascination for luxury glass artwork to its customers through its objects, including Studio Lines, Outdoor Objects and Art Objects. Borowski’s brand message of Love, Passion and Perfection are displayed with each handcrafted pieces. Our website for Borowski Asia Pacific: https://www.borowski-glass.com.hk 博罗夫斯基是一个起源于德国的玻璃艺术品牌。博罗夫斯基将其对豪华玻璃艺术创作的痴迷和热爱通过其作品传递给客户,包括工作室系列、户外系列和艺术家系列。博罗夫斯基品牌的每一个手工艺术作品都向人们传达了爱,激情和完美。我们的中国官方网站:https://www.borowski-glass.cn Our strategy requires to a continues stream of regular English and/or Chinese blog articles related to all topics (glass or home/garden Lifestyle...) relevant to our products. Each blog post will be between 1000 ~ 2000 words per post. 我们需要寻找顶级的英文及/或中文文案为我们定期提供有关博罗夫斯基艺术作品相关的所有主题(包括:玻璃艺术作品,或者家居/花园等格调高雅的生活方式…) 的博客文章等。每篇博文字数在1000 ~ 2000字之间。 It's a long-term work, and if you are an English native speaker or Chinese native speaker (Bilingual is even better), and have experience writing articles or developing/producing any content for any media types, that would be great. 这是一项长期的工作,如果你有丰富的文案创作或具有为任何类型的媒体开发/创作文案内容的经验(熟悉中英文文案创作更佳),请与我们联系。 This project requires: 这个项目要求具有: - Copywriting expertise 文案经验 - Creativity and ability to conceptualize 专业文案创意和概念化的能力 - Familiarity with Glass Artwork (priority at Art Glass topic writing or experience with story tellings about masterworks etc. is preferred) 熟悉玻璃艺术品(有艺术玻璃主题创作或具有艺术故事叙述经验等的将优先考虑) - Familiarity with Home Lifestyle or Garden/Landscape decoration (good taste at new modern Home decoration, Garden decoration or Landscape decoration etc. as to well implement contemporary art into lifestyle...) 熟悉国内的生活方式或园林/景观装饰(具有过人的现代家居装饰,花园装饰或景观装饰品位,能很好地将当代艺术融入极具格调的生活方式当中……) In your proposal, please share a brief summary of your experience and tell us about your most successful copywriting project to date. 请在你的提案中,分享一个简短的经验总结,并告诉我们你迄今为止最成功的文案项目。
4 years ago45 proposalsRemote