ML Hackaton #4 - Machine learning at laptop scale

Join us for the forth session of real practice in Machine Learning and Data Analysis!

In this session we will attempt to find solutions the issues of Learning Convolution Neural networks and Deep learning on the scale of laptops.

Please read carefully the following information and follow the steps.

Note seats are limited please register if you are certain to attend and unregister if you cant make it to free seat for the waiting list.

Step 1: Please take the self assessment

Environment

1. Do you have a Machine Learning environment installed on your computer (Python, R, Scikit-Learn?...) -- Points 3

Exploratory Data Analysis

1. Can you compute mean and variance of your data points' features? -- Points 1

2. Can you perform Histograms? -- Points 2

3. Can you you plot boxplots? -- Points 2

4. Can you compute pivot tables? -- Points 2

5. Can you compute quartiles? -- Points 1

6. Can you segment your data? -- Points 1

Cleaning up Data

1. Can you handle missing data? -- Points 1

2. Can you transform categorical data? -- Points 3

3. Can you process outliers? -- Points 2

Data Modelling

1. Can you perform a regression on data with your computer? -- Points 3

2. Can you perform a classification on data with your computer? -- Points 3

3. Can you perform clustering with your computer? -- Points 3

If you scored 15 or below you may want to join and learn more during the onboarding session

Step 2: Fill the registration form (https://goo.gl/vkXXQQ)

Note without the details provided in the registration form we cant clear you by security for the venue

Note Bloomberg employees are granted special exception from the head count limit please contact Ashley Smart directly and don't sign up using the meetup as the slots are for external attendees only.

Note there maybe Bloomberg press staff present at the event and a standard press release maybe requested

Prerequisites:

• Please bring your laptops

• Please install Python, R or any other language and machine learning tools and libraries which you intend to use

• For beginners please

• install python, pip

• pip install numpy pandas scipy scikit-learn

• A more detail guide is here:

• Ubuntu: http://code-slim-jim.blogspot.jp/2017/03/setting-up-basic-machine-learning-rig.html

• if you run into problems we will attempt to correct the issues on the day but please understand time is limited and we not be able to resolve all the issues, they may be left as an exercise for you to complete during the later stage of the hackaton.

Program:

~10:00: Meet at Tokyo station. Marunouchi South exit (丸の内南口). Please be on time

10:00-10:30 Security check in and Introduction

10:30-13:00 (subject to numbers)

• Advanced Stream: Theme discussion, brainstorming, team forming and Hackaton session 1

• Beginners Stream: Onboarding tuts into basic Machine learning

13:00-14:00 Lunch Break (provided by Bloomberg)

14:00-16:00 Hackaton session 2

16:00-17:00 Reports and results discussion

Fee: Entrance is free and no money can exchange hands due to by due to compliance reasons at the venue.