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During this talk, we'll cover the emergence of big data and what it means to be a data scientist. We'll walk you through how to get the skills to become a data scientist, and focus on the different jobs that will be open to you once you've mastered your new skill set. Agenda: 6:00 pm - 6:20 pm Arrival and mingling 6:20 pm - 6:30 pm Opening words by Murat Baday, CEO of Magnimind Academy, the Meetup sponsors. 6:30 pm - 7:20 pm Fatih Sarigoz, How to transition yourself to a data science career? 7:20 pm - 7:30 pm Q&A About Fatih Sarigoz: His journey started with Signal Processing and Communications, fields very much intertwined with Machine Learning. In fact, his first serious signal processing project was the use of K-means clustering on images (aka Vector Quantization) and later using Neural Networks for binary classification of signals from a data storage channel. At this juncture in his career in Data Science, he feels like having come across an old friend, however now endowed with so many powerful tools and resources. Libraries developed around the R-Studio are amazing. The Python Scikit-Learn package is quite comprehensive. He really enjoys programming in Python which to him is reminiscent of Matlab (and it's free!). What he really hooked up with is the Ipython (now called Jupyter) notebook. Being able to write notes, produce some code and see the results right beneath in a report format lead to fun AND structured learning. There are so many resources out there for anybody to pick up the necessary skills to be a good data scientist. He is truly impressed with the ecosystem built around this new exciting field. He thinks the power of the available material and tools is what enabled him to wade into its deep waters in such a short time. There is so much to learn, but the journey is good. Before diving into "learning" with the "machine" word in front, he has spent the past year trying to build a language learning system in the form of a startup. To him, the process of learning is just fascinating. Teaching what you have learned in fascination is itself fascinating. Things did not work out as he had planned, but he has learned a lot along the way. The journey goes on.
Mindrome Coworking Space & Private Office
Thinking about starting a boot camp or a new field and unsure of your background or level of technical skills? We’ve got you covered. Join our prep course where you’ll learn the necessary prerequisite skills while learning basic data science. This boot camp is for non-coders who are interested in learning data science or those who have a technical background although are not familiar with the fundamentals of data science. This Data Science Prep-Course will teach you the fundamental skills of Python, SQL, Statistics and an introduction to machine learning. With those skills, you will be ready to take any kind of data science boot-camp or you’ll be ready to start learning data science on your own. During our prep course you will explore a hands-on experience that will ignite your enthusiasm and confidence to learn data science and its’ theory. Visit our website to learn detailed information about this boot camp. https://magnimindacademy.com/all-courses/data-science-prep/ Schedule: Start learning the fundamentals of data science with this convenient outside of business hours schedule of 16 hours as follows: Saturday, May 4, 2019 from 10:00 am – 7:00 pm Sunday, May 5, 2019 from 10:00 am – 7:00 pm What You’ll Learn in these 16 hours? 1- Python Explore fundamental data types such as strings, booleans, lists and dictionaries. Learn how to create and organize your code into a clean and professional flow. Learn to analyze data and grow skills to be become a data analyst. 2- SQL Discover how databases are structured, how to add and remove data from a database, and how to query a database, as well as, answer questions using aggregations and joins. 3- Probability and Statistics Model real data using common probability distributions and learn how to infer properties during the data generating process. 4- Linear Algebra Review and refine your linear algebra skills while focusing on relevant topics like vectors and matrices. 5- Data Visualization Most importantly, explore python libraries, tools, Pandas, Numpy, and Matplotlib. Application: We have 30 people attendee limit for this mini boot camp. You can apply through here, or, Via Eventbrite, https://www.eventbrite.com/e/data-science-prep-course-from-magnimind-academy-2-weeks-16-hours-tickets-58976630690 or, use our website to apply and pay at the door. https://magnimindacademy.com/all-courses/data-science-prep/
Mindrome Coworking Space & Private Office
Abstract: So you have heard all the hype around how Machine Learning is going to change the world. You are wondering what does it take to build a machine learning product start to finish in a real-world setting? In this session, you will walk away with a high-level view into a real 0 - 1 product journey. The journey involves deep learning based ML product where we delivered value in record speed in-spite of not having a dataset when we started. You will see a real team in action and also learn what kind of challenges real product teams come across. You will get a sneak peek into how ML pipelines are built and ML services are architected within existing product lines. (You do not need to know deep data science or machine learning for this talk.) Agenda: 6:00 pm - 6:20 pm Arrival and mingling 6:20 pm - 6:30 pm Opening words by Murat Baday, CEO of Magnimind Academy, the Meetup sponsors. 6:30 pm - 7:20 pm Madhura Dudhgaonkar, A Sneak Peek into the World of DEEP LEARNING through a Real 0to1 Product Journey 7:20 pm - 7:30 pm Q&A About Madhura Dudhgaonkar: Madhura Dudhgaonkar is a Machine Learning leader at Workday passionate about modernizing the future of work in a responsible and ethical manner. She is part of the Workday ML organization, a pioneer in the Enterprise Machine Learning space, and has spent 5+ years building ML products leveraging Vision, Natural Language Processing, Recommendations, Anomaly Detection and more. Madhura’s career journey goes from being a hands-on engineer to leading large organizations across SUN Microsystems, Adobe and now Workday. Her background covers building consumer and enterprise products - latest of them involving multiple 0 to 1 product journeys leveraging Machine Learning. She is considered a thought leader in building ML products and is frequently invited to speak at AI conferences.
The two most popular languages for Machine Learning and Data Science are Python and R. As with any computer language, you can't have it all: there are advantages and disadvantages, compromises, and sometimes a bit of ugliness. Clem will do an overview of the two languages so you can get a better feel for which one might be better for your use case, pitfalls and practicalities. Agenda: 6:00 pm - 6:20 pm Arrival and mingling 6:20 pm - 6:30 pm Opening words by Murat Baday, CEO of Magnimind Academy, the Meetup sponsors. 6:30 pm - 7:20 pm Clem Wang, "Python vs. R: The Good, the Bad, and the Ugly" 7:20 pm - 7:30 pm Q&A About Clem Wang: Clem Wang has been a Data Scientist for 15 years, working at both large companies like Yahoo and Microsoft, and a bunch of startups. He's used both Python and R professionally. In a previous life, he's been involved with QA'ing compilers and interpreters, so he has some insights in the inner workings of R and Python.