Including Deep Learning, Reinforcement Learning and AI for Finance tracks, the RE•WORK Summit in Toronto is not to be missed. Visit our website to see the agenda and speaker list!
Data Science Dojo Meetup
What we’ll do:
In this discussion, Raja Iqbal, Chief Data Scientist and CEO of Data Science Dojo, will walk you through the different social applications of AI and how many real-world problems are begging to be solved by data scientists.
You will see how some organizations have made a start on tackling some of the biggest problems to date, the kinds of data and approaches they used, and the benefit these applications have made on thousands of people’s lives.
You’ll learn where there’s untapped opportunity in using AI to make impactful change, sparking ideas for your next big project.
About the Speaker:
Raja Tanveer Iqbal is the Founder of Data Science Dojo, one of the best-rated data science training companies in the world. Data Science Dojo’s mission is to make data science skills accessible to everyone. Raja and his team have trotted the globe to train over 4,000 aspiring data scientists from 775+ companies.
Raja has a Ph.D. in Computer Science with a focus on computer vision and data mining. He worked at Microsoft Corporation for over six years in various roles, solving problems in organic and paid search.
When you attend this Meetup, you enter an area where photography, audio, and video recording may occur. By attending this event, you consent to photography, audio recording, video recording and its/their release, publication, exhibition, or reproduction to be used for promotional purposes, advertising, inclusion on websites, social media, or any other purpose by Data Science Dojo (DSD) and its affiliates and representatives.
Data Science Dojo Meetup
Understanding A/B testing, requires some very basic understanding (and intuition) of Statistics at 101 level. To keep the tutorial self-contained, I will first give an overview of stats fundamentals needed to understand A/B testing. Next, I will explain how A/B testing is done in an online business. In the end, I will mention some of the pitfalls that are common when running online experiments.
This tutorial will roughly be divided into these parts:
• Introducing A/B testing.
• The motivation for running an A/B test. Some examples of how A/B test results are often counter-intuitive. Obama for America campaign and other examples. Multivariate testing
• Statistics fundamentals for hypothesis testing: Null and alternate hypothesis, Factors and levels, confidence intervals, p-values, t-test, sample size, power, Type I and Type II error.
• Art of interpreting metrics: Short-term, medium-term and long-term metrics.
• Common fallacies and pitfalls
2 seats left at 25% OFF!
5 All-Day Courses Data Science Bootcamp
Ivey Donald K Johnson Centre
130 King St W, Toronto, ON M5X 1K6, Canada
- FUNDAMENTALS We emphasize on fundamentals of data exploration, visualization, feature engineering, quality, acquisition and sampling to give you a solid foundation to predictive analytics.
- MACHINE LEARNING The curriculum covers a wide array of classification, regression, recommendation and unsupervised learning techniques. We emphasize on both of solid understanding of algorithms and their correct usage.
- EVALUATION AND PARAMETER TUNING Correct choice of metrics and parameter tuning are essential to building robust predictive models. A combination of lecture, discussion and hands-on labs will ensure that you have the ability to choose the right metrics for your model and you can tune your machine learning model to make it more generalizable.
- BIG DATA AND STREAMING ANALYTICS Even data scientists need some data engineering skills. You will Hadoop cluster in the cloud, run Hive queries, learn to build message queues and process data in real-time, and build an Internet of Things application.
- And so much more! Click REGISTER for the full details.