Search engines have always been a major way to get traffic for free. That is why you need to do your homework and optimize your site so that it ranks well for the keywords you target.

SEO is still the most powerful way to get traffic for free, and you really need to invest some time and effort in the optimization of your site. SEO is not that difficult and if you want to get familiar with it in a nutshell, check our SEO Tutorial. If you are too busy for that, you can start with the 15 Minute SEO article.

2) Frequently Update the Content of Your Site

If you expected some shocking secrets revealed, you might be a bit disappointed. One of the first steps in getting traffic for free is trivial but vital – get great content and frequently update it.

In terms of SEO, content is king. If your content is good and frequently updated, you will not only build a loyal audience of recurring visitors, who will often come to see what is new; but search engines will also love your site!

3) Take advantage of social bookmarking sites.

Social bookmarking sites (especially the most popular among them) are another powerful way to get traffic for free. If you want to learn how to do it, check the How to get Traffic from Social Bookmarking sites article, where we have explained what to do if you want to get free traffic from sites such as Digg, Delicious, etc.

4) Use your Twitter and Facebook accounts.

Social networks are also a way to get traffic for free. If you are popular on networks, such as Twitter or Facebook, the traffic you get from there can easily surpass the traffic from Google and the other search engines. It is true that building a large network of targeted followers on Twitter and supporters on Facebook takes a lot of time and effort but generally the result is worth.

5) Get links with other sites in your niche.

Another way to get traffic for free is from other sites in your niche. Getting links with other sites in your niche is also good for SEO, especially if you manage to get links without the famous nofollow attribute. But even if the links are nofollow (i.e. they are useless for SEO), they still help to get traffic to your site. If you manage to put your link in a visible place on a site with high volumes of traffic, you can get thousands of hits from this link alone. If you need a list of sites within your niche where you could get backlinks from, check the Backlink Builder tool. However, be careful if you exchange links because linking to bad neighbors can do you a lot of harm.

6) Use any chance to promote your site for free.

Free promotion is always welcome, so don’t neglect it. There are many ways to promote your site for free and some of the most popular ones include free classified ads, submissions to directories, inclusion in various listings, etc. It is true that not all free ways to promote your site work well but if you select the right places to promote your site for free, this can also result in tons of traffic.

7) Create a free product or service.

Content drives most traffic when you offer something useful. There are many types of useful content you can create and they largely depend on the niche of your site. You can have articles with tons of advice, or short tips but one of the most powerful ways to get traffic is to create a free product or service. When this product or service gets popular and people start visiting your site, chances are that they will visit the other sections of the site as well.

8) Use viral content.

Free products and services are great for getting free traffic to your site and one of the best varieties in this aspect is viral content. Viral content is called so because it distributes like a virus – i.e. when users like your content, they send it to their friends, post it on various sites, and promote it for free in many different ways. Viral content distributes on its own and your only task is to create it and submit it to a couple of popular sites. After that users pick it and distribute it for you. Viral content can be a hot video or a presentation but it can also be a good old article or an image.

9) Use offline promotion.

Offline promotion is frequently forgotten but it is also a way to get traffic for free. Yes, computers are everywhere and many people spend more time online than offline but still life hasn’t moved completely on the Web. Offline promotion is also very powerful and if you know how to use it, this can also bring you many visitors. Some of the traditional offline ways to promote your site include printing its URL on your company’s business cards and souvenirs or sticking it on your company vehicles. You can also start selling T-shirts and other merchandise with your logo and this way make your brand more popular.

10) Include your URL in your signature.

URLs in forum signatures are also a way to get traffic for free. There are forums, which get millions of visitors a day and if you are a popular user on such a forum, you can use this to get traffic to your site. When you post on forums and people like your posts, they tend to click the link to your site on your signature to learn more about you. In rare cases you might be able to post a deep link (i.e. a link to an internal page of the site) rather than a link to your homepage and this is also a way to focus attention to a particular page. Unfortunately, deep links are rarely allowed.

Getting traffic for free is a vast topic and it is not possible to list all the ways to do it. However, if you know the most important ways – i.e. the ways we discussed in this article and you apply them properly, it is guaranteed that you will be able to get lots of traffic for free.

Source :www. webconfs. com/

1. Magento

Chances are, if you know anything about eCommerce software you’ve heard of Magento. Magento is one of the biggest names in eCommerce, in general, not just open source.

Magento is incredibly flexible and capable – in the hands of the right person/team, it can create a beautiful website for even the largest of retailers. However, all that power comes with a price: Magento is very much intended for expert coders.

You will need to purchase a payment processor, domain name, and security. Magento does not come with built-in security.

2. osCommerce

osCommerce is one of the oldest names in eCommerce software, and as such, a lot has been developed for it. osCommerce has over 7,000 free integrations, and huge active community working on it and giving support for it. Overall, reviewers say that this system is rather outdated to work with, so it takes more finesse. However, much like Magento, if you can figure out how to work with this solution, the world is open to you. There is not much this solution can’t build. You should keep in mind, though, that while osCommerce does have security features, but they’re very weak, so unless you can bolster them, you should probably invest in security software on the side.

3. Open Cart

Open Cart is a rather new solution available – it’s only been around since 2007. For open source, that can sometime spell trouble. After all, as a community developed project, it takes time for the solution to become more complex. But it can also be a good thing – there isn’t as much code to weigh the software down, and it’s still quite simple. In the case of Open Cart, users seem to be split down the middle in which experience they have with open cart. Some people really love it and some people really hate it. If you check this reviews page out, you’ll notice that nearly all of the reviews are either five stars or one. There are only a few that are in between.

Overall, Open Cart is noted for having a sleek administrative dashboard and its general out-of-the-box ease of use. To make a fancy store, you will have to devote some time to the coding, but small stores could potentially use this solution because it does function surprisingly well out of the box.

4. WooCommerce

WooCommerce is a unique solution on this list, because it’s not actually a full open source eCommerce solution on its own. WooCommerce is actually an open source WordPress shopping cart plugin.

So why’s it on here? Well, WordPress is one of the most popular, if not the most popular, content management solutions. There are a LOT of websites built on WordPress. WooCommerce is the open source plugin that those sites can use to turn their site into a store. Of course, if you don’t already have a site, you can still use WooCommerce – you just have to download WordPress first.

What do you need to know about WooCommerce? A few things:

• If you’re used to working with WordPress already, WooCommerce is a breeze to use. It’s fully functional right out of the box and requires little customization. Of course, for those who aren’t used to working with WordPress, there is a bit of a learning curve. Fortunately, there are a lot of resources out there on how to beat WordPress’s learning curve.

• You basically have to use WooCommerce’s templates to get a template to work, so that makes things less flexible.

• In fact, the flexibility over all of WooCommerce is rather limited. It will certainly never be able to create a deeply unique store in the same way Magento can, but that’s the price you pay for ease-of-set-up.

• One very popular feature of WooCommerce is their one-page checkout process. It’s totally unique to Woo, and I’m a fan.

5. SimpleCart

SimpleCart is, as its name suggests, probably the easiest solution to use on this list. Their motto is, “All You Need to Know is HTML,” and according to reviews, that is true. As a result, this might be the best solution on this list for small stores.

A few key features:

• SimpleCart has a very small footprint, so it runs fast. Which, as we all know, is important in the eCom world where every second spent loading loses 7% of your customers.

• Because you will be using HTML to set up your store, SimpleCart is language agnostic.

• It also supports a wide array of currencies. Basically – if you’re not doing business in the US, the language and currency flexibility might make this an ideal solution for you.

• Last thing, SimpleCart has poor security so invest in some security software!

6. PrestaShop

PrestaShop is a rather unique open source solution in that there is actually a for-profit company based around it. How does that work? Basically, PrestaShop’s code is available for free download, same as any other solution. However, PrestaShop has an entire shop of add-on integrations and modules, some of which are free, and some of which are a one-time fee. It’s interesting to note that many of the paid modules are created and sold by community members. In addition, PrestaShop offers its services as a developer. That way, you don’t need to go hunt down a developer who knows how to work with PrestaShop – you can just pay them to set up the shop for you. Over the lifetime of your store, as well, you can continually go back to them, not just community support, for training and help.

Source:www. blog. capterra .com

Machine translation services such as Google Translate have mostly used a “phrase-based” approach of breaking down sentences into words and phrases to be independently translated. But several years ago, Google began experimenting with a deep-learning technique, called neural machine translation, that can translate entire sentences without breaking them down into smaller components. That approach eventually reduced the number of Google Translate errors by at least 60 percent on many language pairs in comparison with the older, phrase-based approach.

Google Translate has already begun using neural machine translation for its 18 million daily translations between English and Chinese. In a here Google researchers also promised to roll out the improved translations to many more language pairs in the coming months.

The deep-learning approach of Google’s neural machine translation relies on a type of software algorithm known as a recurrent neural network. The neural network consists of nodes, also called artificial neurons, arranged in a stack of layers consisting of 1,024 nodes per layer.

A network of eight layers acts as the “encoder,” which takes the sentence targeted for translation—let’s say from Chinese to English—and transforms it into a list of “vectors.” Each vector in the list represents the meanings of all the words read so far in the sentence, so that a vector farther along the list will include more word meanings.

Once the Chinese sentence has been read by the encoder, a network of eight layers acting as the “decoder” generates the English translation one word at a time in a series of steps. A separate “attention network” connects the encoder and decoder by directing the decoder to pay special attention to certain vectors (encoded words) when coming up with the translation. It’s not unlike a human translator constantly referring back to the original sentence during a translation.

This represents an improved version of the original encoder-decoder method that would compress the starting sentence into a fixed-size vector, regardless of the original sentence’s length. The improved version was presented in a paper that includes Cho as coauthor. Cho, who is not affiliated with Google, explains the less accurate original encoder-decoder method as follows:

If I made an analogy to a human translator, what this means is that the human translator is going to look at a source sentence once, memorize the whole thing and start writing down its translation without ever looking back at the source sentence. This is both unrealistic and extremely inefficient. Why wouldn’t a translator look back at the source sentence over and over?

Google started working on neural machine translation several years ago, but the method still generally proved less accurate and required more computational resources than the old approach of phrase-based machine translation. Better accuracy often came at the expense of speed, which is problematic for Google Translate users, who expect almost instantaneous translations.

Google researchers had to harness several clever work-around solutions for their deep-learning algorithms to get beyond the existing limitations of neural machine translation. For example, the team connected the attention network to the encoder and decoder networks in a way that sacrificed some accuracy but allowed for faster speed through parallelism—the method of using several processors to run certain parts of the deep-learning algorithm simultaneously.

“We believe some of our architectural choices are quite unique, mostly to allow maximum parallelism during computation while achieving good accuracy,” Schuster explains.

Another innovation helped neural machine translation handle certain rare words. Part of Google’s solution to this came from the previous work of Schuster and his colleagues on improving the Google Japanese and Korean speech recognition systems. They figured out how to break down rare words into a limited set of smaller, common subunits called “wordpieces,” which the neural machine translation could handle more easily.

A third innovation came from using “quantized computation” to reduce the precision of the system’s calculations and therefore speed up the translation process. Google’s team trained their system to tolerate the resulting “quantization errors” that could arise as a result. “Quantized computation is generally faster than nonquantized computation because all normally 32-bit or 64-bit data can be compressed into 8 or 16 bits, which reduces the time accessing that data and generally makes it faster to do any computations on it,” Schuster says.

Google’s neural machine translation also benefits from running on better hardware than traditional CPUs. The tech giant is using a specialized chip designed for deep learning called the Tensor Processing Unit (TPU). The TPUs alone helped speed up translation by 3.5 times over ordinary chips.

When combined with the new algorithm solutions, Google made its neural machine translation more than 30 times faster with almost no loss of translation accuracy. That huge speed boost made the difference in Google’s decision to finally begin using the deep-learning algorithms for Google Translate in Chinese-to-English translations. The results seem impressive enough to outside experts such as Cho.

“I am extremely impressed by their effort and success in making the inference of neural machine translation fast enough for their production system by quantized inference and their TPU,” Cho says.

Google Translate and other machine translation services still have room for improvement. For example, even the upgraded Google Translate still messes up rare words or simply leaves out certain parts of sentences without translating them. It also still has problems using context to improve its translations. But Schuster seems optimistic that machine translation services will continue to make future progress and creep ever closer to human capabilities.

“If you look at the history of machine translation, you see a constant uptick of translation quality and speed, and we only see this [continuing] until the system is as good as a human in communicating information from one language to another,” Schuster says.