Viruses, trojans, and other malicious programs are everywhere. There's always a new threat to your computer's security, and many of these threats invade your computer without you even knowing. Most viruses aren't going to loudly announce themselves, so it's important to know the hidden ways in which your computer can become infected.


Infected Files from Other Computers

Whether you're borrowing someone's flash drive or grabbing a file from their computer, your computer can become infected if the file or device you're using already contains a virus, trojan, or other form of malware.

This is a very common issue, and you won't even know there's a problem most of the time. For example, if your computer is connected to other devices on a network, and you decide to pull an important file off of another computer on the network, your computer will become infected if the file you took has a virus attached to it.

Also, if you forgot your flash drive, and you need to use your friend or coworker's device for the day, then even plugging the device into your computer can cause the infection in the flash drive to be transmitted.


Downloading Legitimate Programs

Another way your computer can be secretly infected is when you download a legitimate program and run it. There are numerous legitimate programs on the internet that can help you in many ways. The programs themselves could be infected, though.

Also, one of the most common ways your computer can become infected is when you don't read the fine print before you download a program. Some of them may insist that you install another small program in addition to the one you initially chose. The boxes that you are supposed to click to give your consent may already be clicked.

This small extra program is the one that may carry an infection that will spread to your computer when you run the main program. You may get a lot of good use out of the legitimate program, but the virus attached to the extra hidden program can cause you a lot of trouble.


Using Vulnerable Applications

Security is a serious matter. If even one of the applications you use on your computer is vulnerable to becoming hacked or infected, then your entire computer is at risk and could become secretly infected. Anything from PDF viewing applications to your operating system can become infected if you don't download the latest security patches and keep everything up-to-date.


Not Using Antivirus Software

Antivirus software can protect your computer from a number of viruses, trojans, and other problems. Your computer can become infected in a number of ways, so you need to have good antivirus software to provide strong protection from hidden attacks.


Viruses, trojans, and other malware can infect your computer in a variety of hidden ways. To prevent infection and problems, you need to be careful about what you download, and you should keep your applications secure. Also, find reliable antivirus software to help.

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Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.

Due to the advancements in technology, teens and adults alike can now partake in virtual worlds thanks to video games. Video games are enjoyed as a hobby all over the globe, but some gamers have made it their career with help from the ever-growing e-sport community. This is an inside look at the professional level of gaming from an ex-MLG participant, and what I remember going through when starting to play video games at an elite level.

One of the premiere and most popular leagues within the United States happens to be Major League Gaming or MLG for short. This is a league that usually involves more of the most recent games out, and they create circuits for each major title and its subsequent releases. Two of the most major game circuits within the MLG league were the Halo series and the Call of Duty series, both which happened to be first person shooters (FPS). There were a potential hundred or so teams within each circuit, but much like other competitions, the circuits were ran with winner’s brackets and losers brackets. This means that out of all the teams that would show up to MLG events, about the top eight of each bracket would really be known as the "elite" players. I personally played in the Gears of War circuit at venues like MLG Raleigh and MLG Toronto, and we had very few teams compared to Call of Duty and Halo. The amount of participants at each event usually varies in each circuit based on the popularity of the game being played.

When you win tournaments, the payouts are split between the team members. This means that looking at playing in the MLG for a life career is an ill-advised move. The cost to get to events and buy team passes usually negates the prizes you win most of the time, considering by the time that the prize money is split you are left with about $800 in a popular circuit (Like Call of Duty). The payouts are usually only high in special and certain occasions, one for example being the million dollar showdown that Infinity Ward hosted for Call of Duty: Modern Warfare 3 a couple years back. The way that players that make professional gaming their career get the big money now is by being sponsored by the big companies that back the league like Red Bull and Hot Pockets. MLG players like "Walshy" and "FeaR Moho" were sponsored early on in the league and were able to make a living off of the games they played. I would imagine them getting around $60K in a good year off of sponsors alone. I would go even as far as to say that if you do not have a sponsor in e-sports, you will not be financially successful in the career.

Being an MLG gamer requires passion and understanding for the games. If you just want to make money, then you are better off working at McDonalds.

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Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”