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You will get any type of API integrations and developments using php
Project details
I will do any kind of api integrations using php, ajax, javascript etc
I will work on,
social media apis - facebook, linkedin, twitter, youtube etc
location data apis - yelp, foursquare, google etc
forex and currency apis - gdax, bittrex, poloniex etc
ecommerce apis - shopify, woocommerce, chinavasion etc
and any type of API integrations using PHP
You don't have to search somewhere else, you will get the best and the sunniest quality services just in one click and get your work done.
I will work on,
social media apis - facebook, linkedin, twitter, youtube etc
location data apis - yelp, foursquare, google etc
forex and currency apis - gdax, bittrex, poloniex etc
ecommerce apis - shopify, woocommerce, chinavasion etc
and any type of API integrations using PHP
You don't have to search somewhere else, you will get the best and the sunniest quality services just in one click and get your work done.
Programming Languages
PHP, HTML & CSS, JavaScriptCoding Expertise
Cross Browser & Device Compatibility, Performance Optimization, DesignWhat's included
| Service Tiers |
Starter
$100
|
Standard
$150
|
Advanced
$290
|
|---|---|---|---|
| Delivery Time | 1 day | 4 days | 7 days |
Number of Revisions | 1 | 1 | 1 |
Number of Pages Mined/Scraped | 1 | 3 | 4 |
Number of Sources Mined/Scraped | 1 | 3 | 4 |
Install Script | |||
Test Script | |||
Task Automation |
About Ayoub
Data Engineer | Data Analytics (1M+ Records) | Python, SQL
Ksar El Kebir, Morocco - 3:33 am local time
𝟴,𝟬𝟬𝟬+ 𝗷𝗼𝘂𝗿𝗻𝗮𝗹𝗶𝘀𝘁 𝗽𝗿𝗼𝗳𝗶𝗹𝗲𝘀 → AI pipeline (BART zero-shot) classifying journalists by topics/niches into structured taxonomy (80–90% accuracy).
𝟮𝟬% 𝗳𝗮𝘀𝘁𝗲𝗿 𝗾𝘂𝗲𝗿𝗶𝗲𝘀 → Optimized Lambda pipeline (Kafka + batch ETL) and PostgreSQL Warehouse (schema design, indexing, query tuning).
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ℂ𝔸𝕊𝔼 𝕊𝕋𝕌𝔻𝕐
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✦ 𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀:
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⛔ Data ingested from heterogeneous sources (CSV exports, scraped HTML, APIs) with no validation or normalization layer.
⛔ Identical entities stored under multiple variants (e.g., "AI", "Artificial Intelligence", "A.I.", "Ai"), breaking grouping and filtering logic.
⛔ High duplication rate due to lack of deduplication rules or canonical IDs across datasets.
⛔ Encoding issues and malformed text (e.g., "Décor" instead of "Décor") impacting search accuracy.
⛔ Inconsistent schema: missing fields, nested JSON strings, and non-standardized formats across records.
⛔ No controlled taxonomy, leading to 1000s of loosely defined categories with no hierarchy
✦ 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗲𝗱 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻:
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end-to-end data pipeline handling diverse formats (HTML, PDFs, emails, scraped content), with a full cleaning and normalization layer (deduplication, encoding fixes, standardization), an NLP classification pipeline (BART zero-shot) to turn messy sectors into structured categories, structured entity extraction (locations, topics, contacts), and a search-ready indexing layer enabling fast filtering and segmentation.
✦ 𝗧𝗵𝗲 𝗥𝗲𝘀𝘂𝗹𝘁:
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85–90% classification accuracy across ~8,000+ sector entries
Search precision significantly improved, with more relevant matches and stable facet counts in Apache Solr
End-to-end processing pipeline reduced data preparation time from hours to minutes per dataset
Consistent category structure enabled scalable filtering, aggregation, and downstream analytics
Segmentation became reliable enough to support targeted outreach campaigns at scale
System now handles continuous data ingestion without degrading data quality
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SERVICES
✅ Data Engineering
✅ AI/ML
✅ AI Adoption & GenAI
✅ Predictive analytics
✅ High-load Data Scraping
✅ Data Integration - seamless connection through APIs
✅ Data Management – ETL pipelines, Data Warehousing, Data Lakes, DataOps
✅ IT Infrastructure & Solution Architecture
✅ DevOps for Performance Optimization and Cost Reduction
STACK & TECHNOLOGIES
Core stack: Python
Data Warehousing: Redshift | BigQuery | Snowflake | Teradata
Data Lakes: Hadoop | Amazon S3 | Azure Data Lake Storage | Google Cloud Storage
ETL Tools and Data Pipelines: Databricks Workflows | AWS Glue | Google Cloud Dataflow
Big Data Processing: Spark | Hadoop | Google Dataflow | Dask | Amazon Kinesis | Kafka
Databases: MySQL | PostgreSQL | Google BigQuery | MongoDB | DynamoDB | Redis
Using an Agile approach, we ensure fast, reliable, and high-quality product delivery. We back our work with service guarantees, NDA protection, and dedicated post-delivery support.
Want to work together?
I’d love to hear from you!
Steps for completing your project
After purchasing the project, send requirements so Ayoub can start the project.
Delivery time starts when Ayoub receives requirements from you.
Ayoub works on your project following the steps below.
Revisions may occur after the delivery date.
receive requirements from the client
Integration and Coding