Thu, Oct 14 2021 at 06:00 PM at Remote Meeting
(10 Minutes)
By: Meygha Machado
Experience Level: Novice
Automated tests are a great way to iterate fast and ensure features didn't break. This talk discusses how to speed up your builds and dev cycle even more by running tests asynchronously using a pytest plugin called asyncio-cooperative.
(10 Minutes)
By: Shashank Katyayan
Experience Level: Intermediate
Easy to build Python Dashboards using Financial data APIs
Thu, Sep 16 2021 at 06:00 PM at Remote Project Night (chipy.town)
Thu, Sep 09 2021 at 06:00 PM at Remote Meeting (Gather Town)
2021-08-12 18:00:00 location TBD
(50 Minutes)
By: Zax Rosenberg
Experience Level: Intermediate
Building machine learning (ML) models is faster and easier now than ever before. The proliferation of open-source libraries means data scientists can leverage cutting-edge pre-trained models in just a few lines of code. Yet it remains true that most ML models never make it to production. Why? Because making it to production (and staying in production) are about more than just model and code quality. In particular, this talk will discuss how MLOps can greatly accelerate and increase the chances of model success.
Specifically, the talk will walk through the full ML lifecycle and answer: What is MLOps? Why is it important? How can MLOps infrastructure be set up quickly, easily, and with open source tools? How can the system be designed in a user-friendly way, but without too much magic? How can user adoption be accelerated?
While its expected that data-science-related professionals will garner the most value from this talk, no prior MLOps/ML background is required to understand the contents of the talk.
(20 Minutes)
By: Manaswita Tyagi
Experience Level: Novice
In Today’s world, AI has become an essential tool for achieving and creating the unthinkable. It is helping in creating innovative solutions for almost every industry there is. In the wake of this ever-growing demand for computerized intelligence, what constitutes an active research domain is how AI-based intelligence can be interpreted and utilized by HR (Human Resources) from predictive analysis to automation. As the HR department is solely responsible for recruiting and bringing valuable talent to the industry, it becomes essential that this task is done with maximum efficiency. Through this project, we intend to predict which employee would prefer a job change and which employee would stay in a company and help assess the input resources required to put in an employee. This presentation will take you through the principles of using python, opinion mining, and various widely used classifiers, namely Random Forest (RF), Cat Boost Classifier, Support Vector Machine (SVM), and Naìˆve Bayes (NB).