Voice over a 11min presentation video ZDLTK53306522172X
I'm making the promotional video for our start up company called "Binary Options Signals Indicator". I finished the pictures of the video but for the sound I had to use my voice with my terrible french accent. Therefore I'd like a proffesional american voice instead. You can check it there ********************************
2012-08-07 20:20:14 GMT
2012-08-10 16:18:51 (GMT -05:00) Eastern Time (US & Canada)
Yes (click here to learn more about )
Closed - Note: This project was manually closed by the voice seeker before it reached its original deadline.
000 direct invitation(s) have been sent by the voice seeker resulting in 0 audition(s) and/or proposal(s) so far.
Voice123 SmartCast is seeking 50 auditions and/or proposals for this project (approx.) Invitations sent by SmartCast have resulted in 0 audition(s) and/or proposal(s) so far.
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• Deliver edited and finished voice tracks AND • Provide voice direction
The voice seeker is willing to hire either union or non-union talents for this project
Yescustom demo required
Ok, to finish, I also wanted to really quickly show you what was inside the indicator, because it’s a nice black box with a really simple and easy to use interface, but on the inside, it’s a complete other story. In fact the indicator has been developed by two PhDs working in the field of military robotics. What they did basically is take the machine learning algorithms they were using on robots and tried to apply them to trading binary options, and it worked! More precisely, they took every 15 minutes candles over the past 10 years and at the opening of each candle, they computed every possible indicator they could think of: RSI, MACD, Volatility, Support and Resistance, bulls’ power, bears’ power, etc… and for each indicator they tried every possible parameters. MACD 5 8 9, 5 8 10, 5 8 11, or even 10 40 200. It gave them a huge table of 4 million lines corresponding to every 15min candles and 100,000 columns corresponding to every indicators and parameters. Then they applied machine learning algorithms on clusters of computers to crush the data and find patterns in it. They first applied an algorithm called Principal Components Analysis to find the predominant indicators, then Expectation Maximization Clustering to find the patterns in those indicators, then REP Tree Classification to find the rules defining these patterns, and finally Polynomial Interpolation to define the equations defining the rules defining the patterns in the predominant indicators. "Pheewww". Well, what matters is that at the end it gave them a mathematical equation that outputs the probability of an opening candle to belong to one of the patterns and therefore to go up or to go down.
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83194Sign in to display the company name (if applicable)2012-08-071 0
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