Freelancer 로고
로그인 회원 가입
프로젝트 등록
탐색
Data Mining
Data Processing
Machine Learning (ML)
Statistical Analysis
Web Scraping
프로필 배경 사진
를 팔로우 했습니다.
팔로우 서비스의 지정 과정에서 문제가 발생하였습니다.
이 사용자의 경우에는 다른 사용자들의 팔로우 서비스를 허용하지 않고 있습니다.
이 사용자에 대한 팔로우 서비스를 이미 이용하고 계십니다.
고객님의 현재 멤버십 등급으로는 0 건까지만 팔로우가 가능합니다. 멤버십 서비스의 업그레이드는 여기에서 하시면 됩니다.
성공적으로 언팔로우했습니다
팔로우 서비스에 대한 지정 해제 과정에서 문제가 발생하였습니다.
님에 대한 고객님의 추천 절차가 모두 완료되었습니다.
사용자 추천 과정에서 문제가 발생하였습니다.
원인을 알 수 없는 문제가 발생하였습니다. 현재의 페이지에서 다시 읽기 버튼을 클릭하신 후에 재시도하여 주시기 바랍니다.
이메일에 대한 인증 절차가 완료되었습니다.
사용자 아바타

Hammad R.

@hammad40241

monthly-level-two.svg
5.0
3
3.0
3.0
100%

Data Science| AI Dev | Prompt Eng | RAG | Chatbots

$15 USD / 시간
・
국기 ()
Pakistan (8:19 PM)
・
8월 24, 2023에 가입
$15 USD / 시간
・
I specialize in delivering advanced solutions in data science, AI, deep learning, machine learning, natural language processing (NLP), large language models (LLM), retrieval-augmented generation (RAG), computer vision, and fine-tuning. I'm committed to driving innovation and excellence, transforming complex challenges into actionable insights. Partner with me to unlock the full potential of AI and elevate your business to new heights. Discover the future of intelligent solutions with my expertise.
인증
제시간에
100%
예산 금액 내에
100%
금액 수락
100%
Freelancer Data Processing Executives Pakistan
Data Processing Executives 분야의 전체 프리랜서 확인 (대상 국가: Pakistan)

포트폴리오

포트폴리오

12393948
Built an AI-powered chatbot for a leading bank to make internal processes smoother and help employees get quick answers. The chatbot is based on RAG and comes with features like: 1. Policy Assistance: Answers common questions about bank policies, leaves, perks, reimbursements, and retirement plans. 2. Leave Applications: Helps employees create leave forms in just a few clicks. 3. Claim Applications: Makes it easy to generate forms for claims like mobile, petrol, and insurance. 4. Personalized Responses: Provides replies tailored to each employee’s specific needs.
AI Banking Assistant for Employee
11350032
I developed a script to scrape emails from a client's LinkedIn account. This tool automates the extraction process, ensuring accurate and efficient data collection
Scrape Emails from Client LinkedIn
12112511
We developed an AI Document Navigator (AIDN) to help a client efficiently retrieve information from large sets of PDFs and JSON files. Our goal was to enhance document access, making it faster and more accurate with advanced AI technologies. A key challenge was handling large documents without slowing down. We optimized document splitting and retrieval processes for quick responses. We also created a context-aware retriever for more relevant information. We used OpenAI's GPT-4 for language processing, FAISS for vector storage, and implemented recursive text splitting for document chunking. We also employed robust security measures to manage environment variables.
RAG Chatbot: LangChain & Chainlit
11319414
To calculate the Customer Lifetime Value (LTV) for a U.S. firm, we first analyzed historical data to determine the Average Purchase Value (APV). This involved dividing the firm's total revenue over a specific period by the number of purchases in that period. Next, we calculated the Average Purchase Frequency Rate (APFR) by dividing the total number of purchases by the number of unique customers. Multiplying APV with APFR gave us the Customer Value. Then, we estimated the Average Customer Lifespan (ACL) by analyzing the duration of customer relationships. The LTV was calculated by multiplying Customer Value with ACL. This process provided insight into how much revenue a customer would bring over their relationship with the firm. By understanding LTV, the company can make informed decisions on customer acquisition and retention strategies.
"Calculate CLV for US sports firm"
To calculate the Customer Lifetime Value (LTV) for a U.S. firm, we first analyzed historical data to determine the Average Purchase Value (APV). This involved dividing the firm's total revenue over a specific period by the number of purchases in that period. Next, we calculated the Average Purchase Frequency Rate (APFR) by dividing the total number of purchases by the number of unique customers. Multiplying APV with APFR gave us the Customer Value. Then, we estimated the Average Customer Lifespan (ACL) by analyzing the duration of customer relationships. The LTV was calculated by multiplying Customer Value with ACL. This process provided insight into how much revenue a customer would bring over their relationship with the firm. By understanding LTV, the company can make informed decisions on customer acquisition and retention strategies.
"Calculate CLV for US sports firm"
12112538
We analyzed automotive sales data spanning from April 2007 to May 2023 across GCC countries such as Saudi Arabia, Kuwait, the United Arab Emirates, Qatar, Bahrain, and Oman. Through extensive visualization, we delved into the sales performance of various manufacturers and car segments. Our findings uncovered compelling trends and patterns in the GCC automotive industry over sixteen years. Notably, certain manufacturers consistently dominated the market, while others experienced sales fluctuations. These insights offer valuable guidance for industry stakeholders and policymakers, aiding in informed decision-making and strategic planning for the future of the automotive market in the GCC region.
Exploring Automotive Sales Trend
12112527
The AI Tax Law Assistant is a smart chatbot, trained on hundreds of PDFs covering Pakistan's tax laws. Developed with a leading government firm, this tool provides clear and quick legal help, using advanced AI to handle Pakistan's tax rules. The government firm used this assistant to make their tax advisory services faster and more accurate. The assistant has a huge knowledge base from laws, case studies, and guidelines, ensuring it understands Pakistan's tax laws well. It uses advanced language processing to understand user questions in everyday language and gives clear, simple answers. The chatbot combines information retrieval and generation to provide accurate, up-to-date responses to complex tax questions. Its easy-to-use interface allows anyone to input queries and get instant replies, making it accessible to users of all knowledge levels. The AI Tax Law Assistant offers specific advice based on different scenarios, summarizes long legal documents for quick understanding, and
AI Tax Law Assistant for Pakistan
12393948
Built an AI-powered chatbot for a leading bank to make internal processes smoother and help employees get quick answers. The chatbot is based on RAG and comes with features like: 1. Policy Assistance: Answers common questions about bank policies, leaves, perks, reimbursements, and retirement plans. 2. Leave Applications: Helps employees create leave forms in just a few clicks. 3. Claim Applications: Makes it easy to generate forms for claims like mobile, petrol, and insurance. 4. Personalized Responses: Provides replies tailored to each employee’s specific needs.
AI Banking Assistant for Employee
11350032
I developed a script to scrape emails from a client's LinkedIn account. This tool automates the extraction process, ensuring accurate and efficient data collection
Scrape Emails from Client LinkedIn
12112511
We developed an AI Document Navigator (AIDN) to help a client efficiently retrieve information from large sets of PDFs and JSON files. Our goal was to enhance document access, making it faster and more accurate with advanced AI technologies. A key challenge was handling large documents without slowing down. We optimized document splitting and retrieval processes for quick responses. We also created a context-aware retriever for more relevant information. We used OpenAI's GPT-4 for language processing, FAISS for vector storage, and implemented recursive text splitting for document chunking. We also employed robust security measures to manage environment variables.
RAG Chatbot: LangChain & Chainlit
11319414
To calculate the Customer Lifetime Value (LTV) for a U.S. firm, we first analyzed historical data to determine the Average Purchase Value (APV). This involved dividing the firm's total revenue over a specific period by the number of purchases in that period. Next, we calculated the Average Purchase Frequency Rate (APFR) by dividing the total number of purchases by the number of unique customers. Multiplying APV with APFR gave us the Customer Value. Then, we estimated the Average Customer Lifespan (ACL) by analyzing the duration of customer relationships. The LTV was calculated by multiplying Customer Value with ACL. This process provided insight into how much revenue a customer would bring over their relationship with the firm. By understanding LTV, the company can make informed decisions on customer acquisition and retention strategies.
"Calculate CLV for US sports firm"
To calculate the Customer Lifetime Value (LTV) for a U.S. firm, we first analyzed historical data to determine the Average Purchase Value (APV). This involved dividing the firm's total revenue over a specific period by the number of purchases in that period. Next, we calculated the Average Purchase Frequency Rate (APFR) by dividing the total number of purchases by the number of unique customers. Multiplying APV with APFR gave us the Customer Value. Then, we estimated the Average Customer Lifespan (ACL) by analyzing the duration of customer relationships. The LTV was calculated by multiplying Customer Value with ACL. This process provided insight into how much revenue a customer would bring over their relationship with the firm. By understanding LTV, the company can make informed decisions on customer acquisition and retention strategies.
"Calculate CLV for US sports firm"
12112538
We analyzed automotive sales data spanning from April 2007 to May 2023 across GCC countries such as Saudi Arabia, Kuwait, the United Arab Emirates, Qatar, Bahrain, and Oman. Through extensive visualization, we delved into the sales performance of various manufacturers and car segments. Our findings uncovered compelling trends and patterns in the GCC automotive industry over sixteen years. Notably, certain manufacturers consistently dominated the market, while others experienced sales fluctuations. These insights offer valuable guidance for industry stakeholders and policymakers, aiding in informed decision-making and strategic planning for the future of the automotive market in the GCC region.
Exploring Automotive Sales Trend
12112527
The AI Tax Law Assistant is a smart chatbot, trained on hundreds of PDFs covering Pakistan's tax laws. Developed with a leading government firm, this tool provides clear and quick legal help, using advanced AI to handle Pakistan's tax rules. The government firm used this assistant to make their tax advisory services faster and more accurate. The assistant has a huge knowledge base from laws, case studies, and guidelines, ensuring it understands Pakistan's tax laws well. It uses advanced language processing to understand user questions in everyday language and gives clear, simple answers. The chatbot combines information retrieval and generation to provide accurate, up-to-date responses to complex tax questions. Its easy-to-use interface allows anyone to input queries and get instant replies, making it accessible to users of all knowledge levels. The AI Tax Law Assistant offers specific advice based on different scenarios, summarizes long legal documents for quick understanding, and
AI Tax Law Assistant for Pakistan
변경 내역 저장 완료
5.0 · 3 Reviews
리뷰
W
Write python function to download data from website • €8 EUR
It was an absolute pleasure to work with Hammad. Super! Looking forward to work with you again. Keep it up.
Anoop W.
@waliaanoop
•
국기 ()
Kessel-Lo (Leuven), Belgium
•
25일 전
공유
사용자 아바타
Parse pdf files (Bank statements) into CSV • $10 USD
We got there with this small project. good Work Hammad
Brendan O.
@SmileBCS
•
국기 ()
Belfast, United Kingdom
•
1년 전
공유
사용자 아바타
Pandas / Python help • €234 EUR
Good communication, great efforts en brilliant results
Tim B.
@timovic80
•
국기 ()
Zuid-Scharwoude, Netherlands
•
1년 전
공유
경험
AI Engineer
4월, 2023 - 선물
•
1 , 8
Habibi Group
4월, 2023 - 선물
•
1 , 8
- Fine-tuned Llama2, Mistral, and GPT-3.5 Turbo for domain datasets. - Engineered RAG-based chatbots for optimized interactions with PDFs, websites, and databases. - Managed vector databases (Pinecone, PgVector, Chroma) for efficient embedding storage. - Leveraged LangChain and LlamaIndex for seamless data integration. - Designed and implemented RESTful APIs using Flask, django. - Deployed RESTful APIs on AWS. - Developed ML pipelines for automated data preprocessing, training, and deployment.
국기 ()
karachi, Pakistan
4월, 2023 - 선물
•
1 , 8
Data Scientist
3월, 2022 - 선물
•
2 , 9
Fiverr
3월, 2022 - 선물
•
2 , 9
I have successfully completed over 70 projects on Fiverr encompassing a wide range of areas including data science, machine learning, statistical analysis, web scraping, and computer vision.I have ascended the ranks and am proud to be a Level Two seller on Fiverr.
3월, 2022 - 선물
•
2 , 9
교육
Karachi University
2019 - 2023
•
4
Computer Science
국기 ()
Pakistan
2019 - 2023
•
4
NED University of Engineering and Technology
2020 - 2021
•
1
Industrial Data Science Post Graduate Diploma
국기 ()
Pakistan
2020 - 2021
•
1
자격증
Certified Data Scientist
2021
DataQuest
--
2021
초대장 발송이 완료되었습니다!
감사합니다! 무료 크레딧을 신청할 수 있는 링크를 이메일로 보내드렸습니다.
이메일을 보내는 동안 문제가 발생했습니다. 다시 시도해 주세요.
Freelancer 로고 Korea, Republic of / 한국어
도움말 및 고객 지원
프리랜서
항목프로젝트콘테스트프리랜서기업AI 개발 멤버십우수 프리랜서 프로그램프로젝트 관리지역 일자리Photo Anywhere 쇼케이스 개발자용 API인증 받으세요데스크톱 앱
 기업 소개
Freelancer 소개안내보안투자자사이트맵스토리뉴스팀상금보도 자료경력
 이용 약관
개인정보 보호정책 이용 약관 저작권정책 윤리 수칙수수료 및 요금
협력 단체
Escrow.com LoadshiftWarrior Forum
 앱
애플의 앱 스토어 관련 로고구글 플레이 로고
클립보드로 복사하는 과정에서 문제가 발생하였습니다. 고객님의 권한 정보를 조정하신 후에 재시도하여 주시기 바랍니다.
클립보드로 복사되었습니다.
등록 사용자 전체 등록 건수(일자리)
Freelancer ® is a registered Trademark of Freelancer Technology Pty Limited (ACN 142 189 759)
Copyright © 2025 Freelancer Technology Pty Limited (ACN 142 189 759)
미리 보기 화면을 준비 중...
위치 정보 관련 접근권이 허용되었습니다.
고객님의 로그인 세션이 만료되어, 자동으로 로그아웃 처리가 되었습니다. 다시 로그인하여 주십시오.