All Tutorials

Tutorials

We'll take a first-principles approach in defining a Real-Time AI Platform. Drawing from various examples across the industry, and looking at emerging architectures of some early pioneers.

Tutorials

We'll be outlining some of the various real-time database tools and some of their pros and cons as well as discuss some of the methods developers use to implement real-time solutions. 

Tutorials

Zia Hydari will present his research, investigating gamification, health wearables in combination with gamification, enable interventions that have the potential to increase physical activity-a key determinant of health.

Tutorials

We'll understand how to use machine learning tools for signal processing. We'll discuss Principal Component Analysis (PCA) in particular: data compression and noise removal. 

Tutorials

Azure Custom Vision is an image recognition service that lets you build, deploy, and improve your own computer vision models in the cloud

Tutorials

Overview of various storage systems from Redshift, MySQL, and Hadoop to a list of other data systems used for analytical and operational purposes to take better decisions.

Tutorials

Discussion on real use-cases of NLP in today's world focusing on three major topics in data science: Language Models, Part of Speech, and Word Embeddings.

Tutorials

Discussion on the best practices to follow with the goal of documenting experiments to help reproducibility. The tools startups are working on to fix the gaping issues.

Tutorials

A detailed discussion on what to expect in an interview for a position in the data science job market. Guidelines on how to tackle some unexpected, tricky questions in the interviews.

Tutorials

Everything about the role and responsibilities of a Data Engineer. From data pipelines and storage systems to managing metrics, models, and dashboards, a Data Engineer does it all.

Tutorials

Introduction to standard web scraping commands in R using rvest and guidelines to set up a web-scraping script so as to analyze frequently updated data in a periodic manner.

Tutorials

Discussion on the high-level thinking process of coming up with a machine learning algorithm. The process beings by asking the right questions before going to the tools or technologies.

Tutorials

Introduction to the use of AI for social good. From issues of poverty and social equity to sustainability and environmental standards, AI has the potential to be of great help in the modern world.

Tutorials

The basics of Natural Language Processing, its components, and enterprise applications. Using NLP to build a simple chatbot that can deal with some Frequently Asked Questions (FAQs).

Tutorials

The use of ggplot2 to visualize data with a specific focus on discovering the underlying signals and patterns of a business. Data visualization can then add great value to data analysis.

Tutorials

An introduction to dplyr and its usefulness in data manipulation. The use of dplyr to mung data while demonstrating with a Kaggle dataset on wine ratings.

Tutorials

Discussion on building a business case for machine learning models and working with a new model, followed by a 10-step checklist with examples to build a business model.

Tutorials

Introduction to the common ethical concerns and dilemmas in the field of data science. Possible opportunities for data scientists to move past ethical evils and pave the way for a brighter future.

Tutorials

Introduction to various aspects of feature engineering for bot detection of automated web traffic. Developing an understanding of the impact on online business and types of web bots available.

Tutorials

Overview of the A/B testing technique along with the usefulness of this testing mechanism in an online business. The common issues and pitfalls in A/B testing when running online experiments.