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Machine Learning for
Commercial Projects
by
Abdul Wahid
Who AM I
Abdul Wahid
Founder GleeTech
Co-Founder Polanyio
• Started working as a Software Engineer
in 2005.
• PhD (Machine Learning).
• 2016, Victoria University of Wellington
• Develops intelligent digital products.
• Passionate about
• AI/Machine Learning
• Big Data
• Tech Startups/Businesses
Machine Learning Services
• Computer Vision
• Forecasting
• NLP/Chatbots
• Predictive Analytics
• Deep Learning
• Recommendation Systems
• Market Intelligence
• People Intelligence
• ChatBots
• Intelligent Automation
Recent Machine Learning Projects
• Computer Vision
• Traffic Surveillance
• Object Detection and tracking
• OCR for Receipts
• Barcode App
• Face recognition
• Forecasting
• Demand forecasting for energy data
• Detecting home appliances from energy data (Disaggregation)
• Time series Analysis for Financial data
• NLP
• Malware detection
• Sentiment Analysis
• Entity Recognition and Disambiguation
• Chabots
Traffic Surveillance
Barcode Scanner
• Barcode image recognition
• Native App
OCR for Receipts
Training Data Real Life Data Results
Challenges
• No Data
• AI can do anything
• Too technical even for technical people
• Budget
• High accuracy
• User Experience
• Scalability
• Hardware - GPUs
• AWS too expensive

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Machine Learning for Commercial Projects

  • 1. Machine Learning for Commercial Projects by Abdul Wahid
  • 2. Who AM I Abdul Wahid Founder GleeTech Co-Founder Polanyio • Started working as a Software Engineer in 2005. • PhD (Machine Learning). • 2016, Victoria University of Wellington • Develops intelligent digital products. • Passionate about • AI/Machine Learning • Big Data • Tech Startups/Businesses
  • 3. Machine Learning Services • Computer Vision • Forecasting • NLP/Chatbots • Predictive Analytics • Deep Learning • Recommendation Systems • Market Intelligence • People Intelligence • ChatBots • Intelligent Automation
  • 4. Recent Machine Learning Projects • Computer Vision • Traffic Surveillance • Object Detection and tracking • OCR for Receipts • Barcode App • Face recognition • Forecasting • Demand forecasting for energy data • Detecting home appliances from energy data (Disaggregation) • Time series Analysis for Financial data • NLP • Malware detection • Sentiment Analysis • Entity Recognition and Disambiguation • Chabots
  • 6. Barcode Scanner • Barcode image recognition • Native App
  • 7. OCR for Receipts Training Data Real Life Data Results
  • 8. Challenges • No Data • AI can do anything • Too technical even for technical people • Budget • High accuracy • User Experience • Scalability • Hardware - GPUs • AWS too expensive