Transcript: Title Number Three Here are some bullet points Because everyone loves these Also, mustache Another Title Body of the conclusion. Title Number One subtitle Concluding Title ... and subtitle Insert Title Body of the point With BIGGER points.
Transcript: Nicolas VU HUU EPFL Capstone Project COS Applied Data Science: Machine Learning INTRO Introduction Project background DATA OVERVIEW Feature engineering & EDA Data overview Stock Universe Shortlist Market data Preparation CAR/HTZ ML-friendly IB API Decomposition Alphavantage API ML MODELS Machine Learning models Preparation, training and evaluation Decision Tree Linear regression ARIMA Neural networks CONCLUSION & QUESTIONS Question Time BIBLIOGRAPHY Bibliography Haroon, D. (2017). Python Machine Learning Case Studies; Apress Kristjanpoller, W. D., & Concha, D. (2016). Impact of fuel price fluctuations on airline stock returns. Applied Energy Leshik, E., Cralle, J. (2011), An Introduction to Algorithmic Trading: Basic to Advanced Strategies; Wiley Trading Narang, R. K. (2013), Inside the Black Box: A Simple Guide to Quantitative and High Frequency Trading; Wiley Nielsen, A (2020), Practical Time Series Analysis: Prediction with Statistics & Machine Learning; O'Reilly Nison, S. (1991), Japanese Candlestick Charting Techniques: A Contemporary Guide to the Ancient Investment Techniques of the Far East; New York Institute of Finance Weiming, J. (2019), Mastering Python for Finance; Packt Publishing Web sites Agile Business Consortium https://www.agilebusiness.org Alpha Vantage https://www.alphavantage.co/documentation/ (historical market data API) Credit Suisse https://www.credit-suisse.com/pwp/pb/pb_research/technical_tutorial_de.pdf ("Technical analysis - Explained") Datahub.io (list of NYSE traded stocks) https://datahub.io/core/nyse-other-listings#resource-nyse-listed Finbox screener https://finbox.com/screener (data universe screener) Mplfinance https://github.com/matplotlib/mplfinance Newsapi https://newsapi.org/ Quandl http://www.quandl.com (market data sets) Time Series analysis (TSA) http://www.statsmodels.org/stable/tsa.html
Transcript: and subtitle We have the conclusion. So make any final notes you can think of, within this box. Then make jokes. Tear off your break away pants. Party. Example Title Facebook Twitter LinkedIn Mustache Coalition And Finally, Mega Point #1 Social Media Because who doesn't? With Bullet Points Because People Love Bullet Points Also, Mustaches
Transcript: SmartCard Biweekly Round up Meeting Internship Ewa Tyma 10.09.2019 AGENDA AGENDA 01. 02. 03. Technology and implementation What's next In addition 04. Theory Theory THEORY My Task MY TASK To insure that the produced IDCards are working as designed we need to test all the vital components. To do this we will make a test stand which will be designed to insert the IDCard and have pins that will connect on debugging pads. The PCB will be enclosed in a plastic box after testing. TECHNOLOGY AND IMPLEMENTATION TECHNOLOGY AND IMPLEMENTATION Scheme Python Script WHAT'S NEXT WHAT'S NEXT Finishing the python code Trying to carry out tests Preparation of the test stand IN ADDITION Case for SmartCard
Transcript: Presentation Name. By: Liam Lawrence Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic. Text. Topic. Topic.
Transcript: Title Name of Presenters Date PLACE YOUR LOGO HERE Agenda Agenda 1. 2. 3. Introductory materials Facts Data Graphs Heading #1 Heading #1 Subheading Going into details here Introduce detailed information Insert images, data, etc subheading More related detailed information Heading #2 Deliverables? Heading #2 Graph/Dataset 1 Deliverable #1 1. 2. 3. Insert Data and Graphs here Graph/Data set #2 Deliverable #2 Insert link to website Analysis Reminders Heading #3 Summary Summary A B C Questions Questions
Transcript: Assessment and management of stroke in the pre-hospital setting Sam, Sam, Shawn, Andy, Charlie & Owen WHAT There are three types of stroke: Transiant ischaemic attack (TIA) - Ischemic stroke and Hemorrhagic stroke (Stroke Association, 2017). The World Health Organisation,( 2017) deffines a stroke as, the interruption of the blood supply to the brain, usually because a blood vessel bursts or is blocked by a clot. This cuts off the supply of oxygen and nutrients, causing damage to the brain tissue. what is a stroke? Stroke classification what comorbidities or health risk factors lead to strokes or increase the risk of strokes? why do people experience strokes? why treatment how do we assess and treat stroke? FAST campaign and treatment pre-hospital / hospital epidemiology What are the UK and international statistics on stroke death and survival chart? bla bla bla! how can we as studet paramedics increase the quality of treatment for stroke patients? how References WHO. (2017). WHO | Stroke, Cerebrovascular accident. Available at: http://www.who.int/topics/cerebrovascular_accident/en/ [Accessed 2 Oct. 2017]. Stroke Association. (2017). Types of stroke. Available at: https://www.stroke.org.uk/what-stroke/types-stroke [Accessed 2 Oct. 2017]. Sibson, L. (2017). Stroke assessment and management in pre-hospital settings. Journal of Paramedic Practice, 9(8), pp.354-361. References
Transcript: Quality Production * Many broadcasters = many pictures from the same match * Many broadcasters = different quality, diffferent number of cameras, different cameras, different schemes Brand building * Ekstraklasa positioning - men's tie * Safety stadiums - no riots, danger looking fans, no flares in TV picture * No details of explicite pictures * TV graphics promoting league instead of TV station ads * MRO - we decide what is presented around the match * MRO - time for selfpromotion Sponsorship & Advertising * TV graphics dedicated to league sponsors * MRO - time for our sponsors ( part of packages) Additional posibilities * Extra production between matchdays of Ekstraklasa * Own OB Van: 1. extra production for clubs (camps, tournaments, friendlies, final gala) 2. external production in off season time - winter sports 3. after 6 years less money for Ekstraklasa production or higher quality production Extra service for Ekstraklasa & TV partners * Magazines & highlights * Lifestyle video content for social media * Fun Parks project * LED perimeter boards centralisation every professional league should have in-house TV production ... because it is independency from local TV market control of quality production supporting brand building additional revenues long term value building of the league thesis editing team ENG cameras ENG crew
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