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Best in what way? Best for the computer to learn? Well, that is determined by two things...the algorithm that the computer processor(s) run through to achieve the "machine learning", and the speed/efficiency of that algorithm - since it could be an algorithm that will work but perhaps will take so much time to arrive at a good result that it is ineffective in a practical sense. Now, if you want to ask instead what is the best computer language in which to program algorithms...it is a controversial subject, but overall I would say programming it in a language that is translated well into the machine language which will be running the algorithm, since it must be the best that it can be -- for speed and efficiency. Then, the computer processor(s) speed is/are not hampered by the inefficiency of the choice of code generator or compiler/intrepreter (i.e., in general, the programming language). However, I also suspect that you are asking from a personal point of view, namely, which language should you learn if you wanted to get into this machine learning field...I think majority of people working in the field like Prolog, Lisp, C++, and Java. Also, there are some people programming in Natural Language Programming (NLP) parsing and lexical analysis that prefer computer languages devoted specifically to NLP. NLP and Machine Learning algorithms are often working hand in hand to sift through human language texts of all kinds to glean and summarize information and find relevant correlations that exist between all of the ideas and stories in those texts - some factual info, some opinions. Businesses like this stuff for data mining and finding patterns amongst people's likes and dislikes so that they can market to those preferences. Also, many people like to discover correlations, for instance, that say when certain words are used in a financial article, the chances are that these certain types of stocks will rise in price. Thus data mining is a large reason for the popularity of machine learning. NLP has been around for many years and is the effort behind what many people have sought -- to build a computer helper that they can talk with in a natural way - so much easier than all that typing and thinking of how to pose the question just so. It is the next step in the evolution of an internet search engine -- one that learns the best answers and filters out all the extra stuff and does not present the "irrelevant". My guess is that the programming language choice for machine learning algorithms will become less important than the design of the machine learning algorithms themselves. As time goes forward, the "programming" is being done with visual tools and automatic code generators, and implementing a design of a new machine learning learning algorithm is done with those high level tools where the designers don't necessarily know how it looks in the programming language or in the machine language. An argument can be made that the "programmers" should know the efficiency of their designs of the machine learning algorithms on that hardware - but that is usually left to the people who are specifically designing the code generators - which is something far removed from the fun of designing the machine learning algorithms. Specialization is the nature of these fields. So, some designers will arrive on the scene that don't know anything about programming languages, they just know the algorithms of the specific domain and are constantly improving them using the Algorithm Studio software.
Plans for the new corporation were publicly announced, including the much-criticized strategy of raising capital by issuing public stocks.
The 25N is .22LR, the 25M is .22 Magnum. There are subvariants of each involving different stocks, different barrel length, etc. sales@countrygunsmith.net
Cyrus McCormick invented the Horse-drawn reaper in 1831. It was based on Scottish designs, but differed in that the machine was pulled by horse(s) rather than pushed & the reaped stocks of grain were laid out to one side.
Yes, but it would not be used in a pure form, because it would be too concentrated for a power reactor. In the UK and France plutonium has been used in what is called MOX (Mixed Oxide) Fuel, where plutonium and uranium oxides are mixed to make fuel with roughly the same fissile content as enriched uranium fuel. I don't believe this technique has been used yet in the US,where spent fuel processing is not in operation so the plutonium is not being separated to make it available. However there may be plutonium available from ex-military stocks, and this could be used if required to supplement the amount of U-235 available.
A good place to get information on stocks and options would be through a reputable licensed broker. Any newspaper or television channel focused on business news programming will offer market quotes and information on the indices plus often programming, news and articles about stocks and options.
Program trading is a method of using a computer program to trade many stocks simultaneously, which can be useful for businesses or rich individuals managing a large number of stocks. More information can be found at financial sites such as Investopedia and EconLib.
The first place would be to check with the company you use for your stocks and see if they offer a program or system you can use. Other places to look would be E-trade or websites that allow you to manage your stocks on your own without going thru a broker.
In simple language, stocks are shares in the ownership of a companies. Stocks represents a claim on the company's assets and earnings. As you acquire more stock, your ownership stake in the company becomes greater. Whether you say shares, equity, or stock, it all means the same thing.
Investment program's exist to invest money or other funds into mutual funds, trading accounts, stocks/bonds, and retirement accounts. Depending on the program there may be more investment options.
Sharebuilder is great for people who want to buy, sell and manage stocks. It's also a great program as it allows you to buy individual stocks, rather than large amounts at one time.
If your iPod Touch / iPhone is not jailbroken, it is impossible to remove the stocks app. If your iPod Touch / iPhone is jailbroken, you can use a program such as iFunBox or iPhoneBrowser to delete the Applications/Stocks.App folder. Restart your device and the Stocks app should be history. Be warned though, if you do delete the Stocks app, you could potentially mess up your device to the point where you have to restore it.
An investment program is created to help people save money. Most programs encourage you to make payments into the program on a regular basis. Most invest the money in stocks, bonds, and mutual funds to help your money grow.
there are: Common stocks Preferred stocks 05/08/08 there are: Common stocks Preferred stocks 05/08/08 there are: Common stocks Preferred stocks 05/08/08
There is no difference between penny stocks and cent stocks.
till stocks last
Best in what way? Best for the computer to learn? Well, that is determined by two things...the algorithm that the computer processor(s) run through to achieve the "machine learning", and the speed/efficiency of that algorithm - since it could be an algorithm that will work but perhaps will take so much time to arrive at a good result that it is ineffective in a practical sense. Now, if you want to ask instead what is the best computer language in which to program algorithms...it is a controversial subject, but overall I would say programming it in a language that is translated well into the machine language which will be running the algorithm, since it must be the best that it can be -- for speed and efficiency. Then, the computer processor(s) speed is/are not hampered by the inefficiency of the choice of code generator or compiler/intrepreter (i.e., in general, the programming language). However, I also suspect that you are asking from a personal point of view, namely, which language should you learn if you wanted to get into this machine learning field...I think majority of people working in the field like Prolog, Lisp, C++, and Java. Also, there are some people programming in Natural Language Programming (NLP) parsing and lexical analysis that prefer computer languages devoted specifically to NLP. NLP and Machine Learning algorithms are often working hand in hand to sift through human language texts of all kinds to glean and summarize information and find relevant correlations that exist between all of the ideas and stories in those texts - some factual info, some opinions. Businesses like this stuff for data mining and finding patterns amongst people's likes and dislikes so that they can market to those preferences. Also, many people like to discover correlations, for instance, that say when certain words are used in a financial article, the chances are that these certain types of stocks will rise in price. Thus data mining is a large reason for the popularity of machine learning. NLP has been around for many years and is the effort behind what many people have sought -- to build a computer helper that they can talk with in a natural way - so much easier than all that typing and thinking of how to pose the question just so. It is the next step in the evolution of an internet search engine -- one that learns the best answers and filters out all the extra stuff and does not present the "irrelevant". My guess is that the programming language choice for machine learning algorithms will become less important than the design of the machine learning algorithms themselves. As time goes forward, the "programming" is being done with visual tools and automatic code generators, and implementing a design of a new machine learning learning algorithm is done with those high level tools where the designers don't necessarily know how it looks in the programming language or in the machine language. An argument can be made that the "programmers" should know the efficiency of their designs of the machine learning algorithms on that hardware - but that is usually left to the people who are specifically designing the code generators - which is something far removed from the fun of designing the machine learning algorithms. Specialization is the nature of these fields. So, some designers will arrive on the scene that don't know anything about programming languages, they just know the algorithms of the specific domain and are constantly improving them using the Algorithm Studio software.