Machine Learning using Python (2 days)
17

Saturday, 17 November

10 am – 5 pm +08

GA Singapore, Spacemob

Level 3, 8 Claymore Hill, Spacemob
Singapore
$400 SGD
Regular Ticket
$400 SGD
Total

In Partnership With:

SGInnovate logo

Questions? Read our FAQs

Machine Learning using Python (2 days)

Saif Farooqui Photo


Analytics Lead - Business Integrity, Facebook

17

Saturday, 17 November

10 am – 5 pm +08

GA Singapore, Spacemob

Level 3, 8 Claymore Hill, Spacemob
Singapore
$400 SGD
Regular Ticket
$400 SGD
Total

In Partnership With:

SGInnovate logo

Questions? Read our FAQs

About This Workshop

This two day workshop will introduce participants to data exploration and machine learning techniques. Participants will learn about the data science workflow and will practice exploring and visualising data using Python and built-in libraries. Participants will also explore the differences between supervised and unsupervised learning techniques and practice creating predictive regression models.

Takeaways

After this lesson, you will be able to:

  • Collect data from a variety of sources (e.g., Excel, web-scraping, APIs and others)
  • Explore large data sets
  • Clean and "munge" the data to prepare it for analysis
  • Apply machine learning algorithms to gain insight from the data
  • Visualize the results of your analysis
  • Build your own library and Python scripts
  • Schedule

    10 am

    Day 1 - Developing the Fundamentals - Nov 17 - 10AM - 5PM

    Module 1: Introduction to Machine Learning (2.5 hours)

  • What is machine learning?
  • Installation and update of tools
  • Machine learning algorithms
  • Module 2: Exploring and using data sets (2.5 hours)

  • Learn the steps to pre-process a dataset and prepare it for machine learning algorithms
  • 10 am

    Day 2 - Diving into machine learning - Nov 24 - 10AM - 5PM

    Module 3: Supervised vs. unsupervised learning (2.5 hours)

  • Review of machine learning algorithms
  • Classification, linear regression and logistic regression
  • Random forests, clustering
  • Decision trees
  • Module 4: Model Evaluation (2.5 hours)

  • Feature Engineering and Model Selection
  • Model Evaluation Metrics - Accuracy, RMSE, ROC, AUC, Confusion Matrix, Precision, Recall, F1 Score
  • Overfitting and Bias-Variance trade-off
  • Cross Validation
  • Preparation

    Beginner/intermediate. This workshop is for analysts, product managers, mathematicians, business managers or anyone else that wants to learn about machine learning. A background in computer science, programming, and/or statistics is preferred for this workshop. It is not required but you are expected to be somewhat familiar with the command line tools and how to write simple programs. Recommended that you take the “Python for Beginners” workshop prior to attending this.

    Please register at least 72 hours before the workshop.

    About the Instructor

    Saif Farooqui Photo

    Analytics Lead - Business Integrity,
    Facebook

    Saif Farooqui is a Technical Analytics Lead in the Business Integrity team, which protects users and ensure safe connections between users and businesses. The team's focus on data analysis, machine learning and a robust infrastructure of back-end systems allows them to collaborate effectively with engineering and product teams.

    Prior to working on data science at Facebook, Saif bounced around a fair bit, from consulting to economics research to marketing science and then computer vision, before a teaching position at (drum roll) General Assembly led to the job of his dreams. Ask him about python generators and the temporal considerations of data analysis!

    About Our Partners

    SGInnovate

    As a part of the robust startup ecosystem here, SGInnovate’s mission is to enable ambitious and capable individuals and teams to imagine, start, build, and scale globally-relevant technologies. We back these entrepreneurs through equity-based investments, access to talent, and support in building customer traction. Our efforts are prioritised around deep technologies that are impactful and scalable answers to global challenges, and we partner industry leaders through a series of programmes to strengthen talent capabilities in areas such as Data Analytics, Machine Learning, and Deep Learning.

    Refund Policy

    We understand that, sometimes, plans change. If you can no longer make it to a class or workshop, please email us at least 7 days before the scheduled event date. No refunds will be given to cancellations made within a week of the class or workshop.

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