Machine Learning using Python (2 days)
16

Saturday, 16 June

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)

Kwan Chong Tan Photo


Senior Data Scientist, SparkBeyond

16

Saturday, 16 June

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 students to data exploration and machine learning techniques. Students will learn about the data science workflow and will practice exploring and visualising data using Python and built-in libraries. Students 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 - June 16 - 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 - June 23 - 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
  • Prereqs & 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.

    About the Instructor

    Kwan Chong Tan Photo

    Senior Data Scientist,
    SparkBeyond

    Kwan Chong is currently a Senior Data Scientist at SparkBeyond and has over ten years of experience working with government and commercial organizations internationally in applying data analytics to achieve business outcomes. He previously worked at Booz Allen Hamilton, Palantir Technologies and the Defence Science & Technology Agency, leading and implementing projects to leverage big data analytics and machine learning across a wide range of domains including cybersecurity, financial crimes, and open source intelligence.

    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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