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You will get End to End machine learning solution, deployed and ready for use.
Project details
You will receive a complete, production ready machine learning solution tailored to your specific business needs. I deliver end to end AI systems from predictive customer churn models and computer vision quality control to recommendation engines and NLP chatbots that are fully deployed and integrated into your workflow. My comprehensive approach covers everything from data analysis and model development to deployment and documentation, ensuring you receive a robust, maintainable solution that delivers immediate value from day one.
Machine Learning Tools
Accord.NET Framework, Apache Mahout, Apache Spark, Apache Spark MLlib, Azure Machine Learning, BERT, Caffe, Cloudera, deeplearn.js, Fiddler.ai, Google AutoML, GPT-3, Keras, Microsoft Excel, Microsoft Power BI, MLflow, NLTK, Open Neural Network Exchange, Python, QlikView, R, SciPy, Scrapy, SPSS, XGBoostWhat's included
| Service Tiers |
Starter
$750
|
Standard
$2,500
|
Advanced
$5,000
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 days |
Number of Revisions | 2 | 3 | 4 |
Number of Model Variations | 2 | 2 | 2 |
Number of Scenarios | 3 | 3 | 3 |
Number of Graphs/Charts | 3 | 3 | 3 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | |||
Source Code |
About Takundanashe
End to End MLOps/LLMOps Engineer | 40+ Models Deployed | AWS/GCP/Azure
Harare, Zimbabwe - 2:19 am local time
𝐌𝐲 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 𝐢𝐬 𝐒𝐩𝐥𝐢𝐭 𝐈𝐧𝐭𝐨 𝐓𝐰𝐨 𝐂𝐨𝐫𝐞, 𝐄𝐧𝐝 𝐭𝐨 𝐄𝐧𝐝 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬:
1. 𝑴𝑳𝑶𝒑𝒔 (𝑷𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏 𝑴𝒂𝒄𝒉𝒊𝒏𝒆 𝑳𝒆𝒂𝒓𝒏𝒊𝒏𝒈)
𝑰 𝒃𝒖𝒊𝒍𝒅 𝒕𝒉𝒆 𝒂𝒖𝒕𝒐𝒎𝒂𝒕𝒆𝒅 𝒑𝒊𝒑𝒆𝒍𝒊𝒏𝒆 𝒇𝒓𝒐𝒎 𝒚𝒐𝒖𝒓 𝒅𝒂𝒕𝒂 𝒕𝒐 𝒚𝒐𝒖𝒓 𝒃𝒐𝒕𝒕𝒐𝒎 𝒍𝒊𝒏𝒆. 𝑻𝒉𝒊𝒔 𝒄𝒐𝒗𝒆𝒓𝒔 𝒕𝒓𝒂𝒅𝒊𝒕𝒊𝒐𝒏𝒂𝒍 𝑴𝑳, 𝒄𝒐𝒎𝒑𝒖𝒕𝒆𝒓 𝒗𝒊𝒔𝒊𝒐𝒏, 𝒂𝒏𝒅 𝒇𝒐𝒓𝒆𝒄𝒂𝒔𝒕𝒊𝒏𝒈 𝒎𝒐𝒅𝒆𝒍𝒔.
𝑾𝒉𝒂𝒕 𝑰 𝑫𝒆𝒍𝒊𝒗𝒆𝒓: 𝑨𝒖𝒕𝒐𝒎𝒂𝒕𝒆𝒅 𝒓𝒆𝒕𝒓𝒂𝒊𝒏𝒊𝒏𝒈 𝒑𝒊𝒑𝒆𝒍𝒊𝒏𝒆𝒔, 𝒎𝒐𝒅𝒆𝒍 𝒗𝒆𝒓𝒔𝒊𝒐𝒏𝒊𝒏𝒈 (𝑴𝑳𝒇𝒍𝒐𝒘), 𝒔𝒄𝒂𝒍𝒂𝒃𝒍𝒆 𝑨𝑷𝑰 𝒅𝒆𝒑𝒍𝒐𝒚𝒎𝒆𝒏𝒕 (𝑭𝒂𝒔𝒕𝑨𝑷𝑰/𝑫𝒐𝒄𝒌𝒆𝒓), 𝒓𝒆𝒂𝒍-𝒕𝒊𝒎𝒆 𝒑𝒆𝒓𝒇𝒐𝒓𝒎𝒂𝒏𝒄𝒆 𝒎𝒐𝒏𝒊𝒕𝒐𝒓𝒊𝒏𝒈 (𝑬𝒗𝒊𝒅𝒆𝒏𝒕𝒍𝒚𝑨𝑰/𝑮𝒓𝒂𝒇𝒂𝒏𝒂), 𝒂𝒏𝒅 𝒅𝒓𝒊𝒇𝒕 𝒅𝒆𝒕𝒆𝒄𝒕𝒊𝒐𝒏.
𝑺𝒂𝒎𝒑𝒍𝒆 𝑫𝒆𝒑𝒍𝒐𝒚𝒎𝒆𝒏𝒕𝒔: 𝑪𝒓𝒆𝒅𝒊𝒕 𝒔𝒄𝒐𝒓𝒊𝒏𝒈 𝑨𝑷𝑰𝒔, 𝒓𝒆𝒂𝒍-𝒕𝒊𝒎𝒆 𝒄𝒐𝒎𝒑𝒖𝒕𝒆𝒓 𝒗𝒊𝒔𝒊𝒐𝒏 𝒔𝒆𝒄𝒖𝒓𝒊𝒕𝒚 𝒔𝒚𝒔𝒕𝒆𝒎𝒔, 𝒅𝒆𝒎𝒂𝒏𝒅 𝒇𝒐𝒓𝒆𝒄𝒂𝒔𝒕𝒊𝒏𝒈 𝒑𝒍𝒂𝒕𝒇𝒐𝒓𝒎𝒔, 𝒂𝒏𝒅 𝒂𝒖𝒕𝒐𝒎𝒂𝒕𝒆𝒅 𝑬𝑻𝑳 𝒓𝒆𝒑𝒐𝒓𝒕𝒊𝒏𝒈 𝒅𝒂𝒔𝒉𝒃𝒐𝒂𝒓𝒅𝒔.
2. 𝑳𝑳𝑴𝑶𝒑𝒔 (𝑷𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏 𝑮𝒆𝒏𝒆𝒓𝒂𝒕𝒊𝒗𝒆 𝑨𝑰 & 𝑳𝑳𝑴𝒔)
𝑰 𝒔𝒑𝒆𝒄𝒊𝒂𝒍𝒊𝒛𝒆 𝒊𝒏 𝒕𝒉𝒆 "𝒍𝒂𝒔𝒕 𝒎𝒊𝒍𝒆" 𝒇𝒐𝒓 𝒈𝒆𝒏𝒆𝒓𝒂𝒕𝒊𝒗𝒆 𝑨𝑰: 𝒕𝒂𝒌𝒊𝒏𝒈 𝑳𝑳𝑴𝒔 𝒇𝒓𝒐𝒎 𝒆𝒙𝒑𝒆𝒓𝒊𝒎𝒆𝒏𝒕𝒂𝒕𝒊𝒐𝒏 𝒕𝒐 𝒔𝒆𝒄𝒖𝒓𝒆, 𝒊𝒏𝒕𝒆𝒈𝒓𝒂𝒕𝒆𝒅, 𝒂𝒏𝒅 𝒗𝒂𝒍𝒖𝒂𝒃𝒍𝒆 𝒂𝒑𝒑𝒍𝒊𝒄𝒂𝒕𝒊𝒐𝒏𝒔.
𝑾𝒉𝒂𝒕 𝑰 𝑫𝒆𝒍𝒊𝒗𝒆𝒓: 𝑺𝒆𝒄𝒖𝒓𝒆 𝑹𝑨𝑮 𝒔𝒚𝒔𝒕𝒆𝒎 𝒅𝒆𝒑𝒍𝒐𝒚𝒎𝒆𝒏𝒕, 𝑳𝑳𝑴 𝒇𝒊𝒏𝒆-𝒕𝒖𝒏𝒊𝒏𝒈 & 𝒐𝒑𝒕𝒊𝒎𝒊𝒛𝒂𝒕𝒊𝒐𝒏, 𝑨𝑰 𝒂𝒈𝒆𝒏𝒕 𝒘𝒐𝒓𝒌𝒇𝒍𝒐𝒘 𝒐𝒓𝒄𝒉𝒆𝒔𝒕𝒓𝒂𝒕𝒊𝒐𝒏 (𝑳𝒂𝒏𝒈𝑮𝒓𝒂𝒑𝒉), 𝒂𝒏𝒅 𝒎𝒖𝒍𝒕𝒊𝒎𝒐𝒅𝒂𝒍 (𝒗𝒐𝒊𝒄𝒆/𝒗𝒊𝒅𝒆𝒐) 𝑨𝑰 𝒊𝒏𝒕𝒆𝒈𝒓𝒂𝒕𝒊𝒐𝒏.
𝑺𝒂𝒎𝒑𝒍𝒆 𝑫𝒆𝒑𝒍𝒐𝒚𝒎𝒆𝒏𝒕𝒔: 𝑬𝒏𝒕𝒆𝒓𝒑𝒓𝒊𝒔𝒆 𝒍𝒆𝒈𝒂𝒍 𝑹𝑨𝑮 𝒔𝒚𝒔𝒕𝒆𝒎𝒔, 𝒂𝒖𝒕𝒐𝒏𝒐𝒎𝒐𝒖𝒔 𝒔𝒂𝒍𝒆𝒔 𝒂𝒈𝒆𝒏𝒕 𝒑𝒍𝒂𝒕𝒇𝒐𝒓𝒎𝒔, 𝑨𝑰 𝒄𝒐𝒏𝒕𝒆𝒏𝒕 𝒈𝒆𝒏𝒆𝒓𝒂𝒕𝒊𝒐𝒏 𝒆𝒏𝒈𝒊𝒏𝒆𝒔, 𝒂𝒏𝒅 𝒇𝒊𝒏𝒆-𝒕𝒖𝒏𝒆𝒅 𝒅𝒐𝒎𝒂𝒊𝒏-𝒔𝒑𝒆𝒄𝒊𝒇𝒊𝒄 𝒄𝒉𝒂𝒕𝒃𝒐𝒕𝒔.
𝑾𝒉𝒚 𝑻𝒉𝒊𝒔 𝑴𝒂𝒕𝒕𝒆𝒓𝒔 𝒇𝒐𝒓 𝒀𝒐𝒖𝒓 𝑷𝒓𝒐𝒋𝒆𝒄𝒕:
𝑴𝒚 𝒅𝒖𝒂𝒍 𝒔𝒑𝒆𝒄𝒊𝒂𝒍𝒊𝒛𝒂𝒕𝒊𝒐𝒏 𝒎𝒆𝒂𝒏𝒔 𝒘𝒉𝒆𝒕𝒉𝒆𝒓 𝒚𝒐𝒖 𝒏𝒆𝒆𝒅 𝒂 𝒑𝒓𝒆𝒅𝒊𝒄𝒕𝒊𝒗𝒆 𝒄𝒉𝒖𝒓𝒏 𝒎𝒐𝒅𝒆𝒍 𝒐𝒓 𝒂 𝒄𝒐𝒎𝒑𝒍𝒆𝒙 𝑨𝑰 𝒂𝒈𝒆𝒏𝒕, 𝒕𝒉𝒆 𝒇𝒊𝒏𝒂𝒍 𝒅𝒆𝒍𝒊𝒗𝒆𝒓𝒂𝒃𝒍𝒆 𝒊𝒔 𝒕𝒉𝒆 𝒔𝒂𝒎𝒆: 𝒂 𝒑𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏-𝒓𝒆𝒂𝒅𝒚, 𝒆𝒏𝒕𝒆𝒓𝒑𝒓𝒊𝒔𝒆-𝒈𝒓𝒂𝒅𝒆 𝒔𝒚𝒔𝒕𝒆𝒎. 𝑰 𝒃𝒓𝒊𝒅𝒈𝒆 𝒕𝒉𝒆 𝒈𝒂𝒑 𝒃𝒆𝒕𝒘𝒆𝒆𝒏 𝒅𝒂𝒕𝒂 𝒔𝒄𝒊𝒆𝒏𝒄𝒆 𝒂𝒏𝒅 𝑫𝒆𝒗𝑶𝒑𝒔, 𝒆𝒏𝒔𝒖𝒓𝒊𝒏𝒈 𝒎𝒐𝒅𝒆𝒍𝒔 𝒂𝒓𝒆 𝒑𝒆𝒓𝒇𝒐𝒓𝒎𝒂𝒏𝒕, 𝒎𝒂𝒊𝒏𝒕𝒂𝒊𝒏𝒂𝒃𝒍𝒆, 𝒂𝒏𝒅 𝒄𝒐𝒔𝒕-𝒆𝒇𝒇𝒆𝒄𝒕𝒊𝒗𝒆 𝒊𝒏 𝒕𝒉𝒆 𝒄𝒍𝒐𝒖𝒅.
𝑴𝒚 40+ 𝒑𝒓𝒐𝒋𝒆𝒄𝒕 𝒑𝒐𝒓𝒕𝒇𝒐𝒍𝒊𝒐 𝒊𝒏𝒄𝒍𝒖𝒅𝒆𝒔 𝒅𝒆𝒑𝒍𝒐𝒚𝒆𝒅 𝒔𝒚𝒔𝒕𝒆𝒎𝒔 𝒇𝒐𝒓: 𝑭𝒓𝒂𝒖𝒅 𝑫𝒆𝒕𝒆𝒄𝒕𝒊𝒐𝒏, 𝑳𝒆𝒈𝒂𝒍 𝑫𝒐𝒄𝒖𝒎𝒆𝒏𝒕 𝑨𝒏𝒂𝒍𝒚𝒔𝒊𝒔, 𝑨𝒖𝒕𝒐𝒏𝒐𝒎𝒐𝒖𝒔 𝑺𝒂𝒍𝒆𝒔 𝑨𝒈𝒆𝒏𝒕𝒔, 𝑹𝒆𝒂𝒍-𝑻𝒊𝒎𝒆 𝑪𝒐𝒎𝒑𝒖𝒕𝒆𝒓 𝑽𝒊𝒔𝒊𝒐𝒏, 𝒂𝒏𝒅 𝑴𝒖𝒍𝒕𝒊-𝑨𝒈𝒆𝒏𝒕 𝑾𝒐𝒓𝒌𝒇𝒍𝒐𝒘 𝑨𝒖𝒕𝒐𝒎𝒂𝒕𝒊𝒐𝒏.
𝑪𝒐𝒓𝒆 𝑻𝒆𝒄𝒉 𝑺𝒕𝒂𝒄𝒌: 𝑫𝒐𝒄𝒌𝒆𝒓 | 𝑲𝒖𝒃𝒆𝒓𝒏𝒆𝒕𝒆𝒔 | 𝑭𝒂𝒔𝒕𝑨𝑷𝑰 | 𝑨𝑾𝑺/𝑮𝑪𝑷/𝑨𝒛𝒖𝒓𝒆 | 𝑷𝒚𝑻𝒐𝒓𝒄𝒉/𝑻𝒆𝒏𝒔𝒐𝒓𝑭𝒍𝒐𝒘 | 𝑴𝑳𝒇𝒍𝒐𝒘 | 𝑳𝒂𝒏𝒈𝑪𝒉𝒂𝒊𝒏 | 𝑷𝒐𝒔𝒕𝒈𝒓𝒆𝑺𝑸𝑳 | 𝑨𝒑𝒂𝒄𝒉𝒆 𝑨𝒊𝒓𝒇𝒍𝒐𝒘 | 𝑯𝒖𝒈𝒈𝒊𝒏𝒈 𝑭𝒂𝒄𝒆 | 𝑳𝑳𝑴 𝑭𝒊𝒏𝒆-𝑻𝒖𝒏𝒊𝒏𝒈.
𝑳𝒆𝒕'𝒔 𝒄𝒐𝒏𝒏𝒆𝒄𝒕 𝒕𝒐 𝒅𝒊𝒔𝒄𝒖𝒔𝒔 𝒎𝒂𝒌𝒊𝒏𝒈 𝒚𝒐𝒖𝒓 𝑨𝑰 𝒊𝒏𝒊𝒕𝒊𝒂𝒕𝒊𝒗𝒆 𝒂 𝒓𝒐𝒃𝒖𝒔𝒕, 𝒑𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏-𝒍𝒆𝒗𝒆𝒍 𝒂𝒔𝒔𝒆𝒕.
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