• Machine Learning & Deep Learning Bootcamp: Building Recommender System

    What will you learn? What are recommendation engines? How does a recommendation engine work? Data collection and Data storage? Filtering the data? Content-based filtering and Collaborative filtering The case study in Python using the public dataset Building a collaborative filtering model from scratch Building Simple popularity and collaborative filtering model Building a recommendation engine, and evaluation metrics for recommendation engines Module 1: Evaluating Recommender Systems Module 2: A Recommender Engine Framework Module 3: Content-Based Filtering Module 4: Neighbourhood-Based Collaborative Filtering Module 5: Matrix Factorization Methods Module 6: Introduction to Deep Learning Module 7: Deep Learning For Recommender Systems and scaling up 09:30 – 10:00 Registration 10:00 – 13:00 Machine Learning on Recommender System 13:00 – 14:00 Lunch 14:00 – 18:00 Deep Learning on Recommender System 18:00 – 18:30 Questions Time We will send out the class materials as well as required library 2 weeks before the class, please follow the instruction and get the environment ready before coming to class. - Data scientist who wants robust or learn more different applications Analyst: Companies who would like to offer re-education to their analytics team to their data science team or just upgrade yourself from analyst to data scientist. - Developer, who wants to know more about the algorithm or even think about switching to be the data scientist - Business Intelligence (BI): You are already familiar with statistics, want to understand better machine learning and prediction A bit of knowledge of Python or machine learning will help you but it is not required. Have some familiarity with basic programming concepts or languages or statistics. Therefore, experience in Python or Machine Learning is not required but will help. During the problem-solving sessions, we will solve on the blackboard any kind of problem the audience poses. In a previous workshop, for example, one of the problems was “How can we use Twitter data to predict Bitcoin prices?”. The solution included the full pipeline (from data collection to data storage), to actually solving the problem and hiring the right people. Feel free to contact me with your problems before the workshop date. “Stylianos brings great enthusiasm to his workshop – his interest in all things AI shines through.” – Tim Gordon, Chief Executive at the Liberal Democrats “Stylianos’s bespoke workshop allows for in-depth complicated analytical concepts to be understood in a manageable and easy way. Coving the background of the constant changing world of data science and breaking down the key concepts of data science.” – Dominik Byrne, Investor, Entrepreneur, Advisor You can find more testimonials here: http://tesseract.academy/ ¹ Dr. Stylianos Kampakis is an expert data scientist (with a decade of experience), member of the Royal Statistical Society, an honorary research fellow at the UCL Centre for Blockchain Technologies and startup consultant living and working in London. A natural polymath, with degrees in Psychology, Artificial Intelligence, Statistics, Economics and a PhD in Computer Science from University College London he loves using his broad skillset to solve difficult problems. You can learn more about his work at skampakis.com.

  • Machine Learning Bootcamp: Learn How To Build Dynamic Pricing In Your Product

    This is the next Bootcamp that we are preparing now. If you are interested, please register here: https://beyond-machine.typeform.com/to/OTLAGY If you want to know more about dynamic pricing and how can it be applied in the business. Please take a look here: https://www.youtube.com/watch?time_continue=688&v=cKPaIsOQslo Preparation of the Bootcamp: We will send out the class materials as well as required library 2 weeks before the class, please follow the instruction and get the environment ready before coming to class. - Data scientist who wants robust or learn more different applications - Analyst: Companies who would like to offer re-education to their analytics team to their data science team or just upgrade yourself from analyst to data scientist. - Developer, who wants to know more about the algorithm or even think about switching to be the data scientist - Business Intelligence (BI): You are already familiar with statistics, want to understand better machine learning and prediction A bit of knowledge of Python or machine learning will help you but it is not required. Have some familiarity with basic programming concepts or languages or statistics. Therefore, experience in Python or Machine Learning is not required but will help. During the problem-solving sessions, we will solve on the blackboard any kind of problem the audience poses. In a previous workshop, for example, one of the problems was “How can we use Twitter data to predict Bitcoin prices?”. The solution included the full pipeline (from data collection to data storage), to actually solving the problem and hiring the right people. Feel free to contact me with your problems before the workshop date. “Stylianos brings great enthusiasm to his workshop – his interest in all things AI shines through.” – Tim Gordon, Chief Executive at the Liberal Democrats “Stylianos’s bespoke workshop allows for in-depth complicated analytical concepts to be understood in a manageable and easy way. Coving the background of the constant changing world of data science and breaking down the key concepts of data science.” – Dominik Byrne, Investor, Entrepreneur, Advisor You can find more testimonials here: http://tesseract.academy/ ¹ Dr. Stylianos Kampakis is an expert data scientist (with a decade of experience), member of the Royal Statistical Society, an honorary research fellow at the UCL Centre for Blockchain Technologies and startup consultant living and working in London. A natural polymath, with degrees in Psychology, Artificial Intelligence, Statistics, Economics and a PhD in Computer Science from University College London he loves using his broad skillset to solve difficult problems. You can learn more about his work at skampakis.com.