Tech & Fun

 There are so many different types of Machine Learning systems that it is useful to classify them in broad categories based on: • Whether or not they are trained with human supervision (supervised, unsuper‐ vised, semisupervised, and Reinforcement Learning) • Whether or not they can learn incrementally on the fly (online versus batch learning) • Whether they work by simply comparing new data points to known data points, or instead detect patterns in the training data and build a predictive model, much like scientists do (instance-based versus model-based learning) These criteria are not exclusive; you can combine them in any way you like. For example, a state-of-the-art spam filter may learn on the fly using a deep neural network model trained using examples of spam and ham; this makes it an online, model- based, supervised learning system. Let’s look at each of these criteria a bit more closely. Supervised/Unsupervised Learning Machine Learning systems can be classified according ...

Consider how you would write a spam filter using traditional programming techniques (Figure 1-1): 1. First you would look at what spam typically looks like. You might notice that some words or phrases (such as “4U,” “credit card,” “free,” and “amazing”) tend to come up a lot in the subject. Perhaps you would also notice a few other patterns in the sender’s name, the email’s body, and so on. 2. You would write a detection algorithm for each of the patterns that you noticed, and your program would flag emails as spam if a number of these patterns are detected. 3. You would test your program, and repeat steps 1 and 2 until it is good enough. Since the problem is not trivial, your program will likely become a long list of com‐ plex rules—pretty hard to maintain. In contrast, a spam filter based on Machine Learning techniques automatically learns which words and phrases are good predictors of spam by detecting unusually fre‐ quent patterns of words in the spam examples compared to the ham e...

 Collecting emails is one of the number one ways to have staying power and build a business online for life. Your email list becomes your B USINESS ASSET​ . As you build rapport with your list and they get to know, like and trust you... sales become effortless! You can earn daily by sending one simple email with an offer to a product (affiliate link). First and foremost where do you get the emails? You must build opt in pages and give people a reason to fill in their email. Give them something in exchange. Free giveaway, compelling headline that makes them curious and want more info. via Blog and/or C apture Page Take a look at my blog as an example:

 Ebay is one of the largest online shopping center and has floods of buyers and natural traffic on a daily basis. The great thing about dropping is you don’t have to stock any physical products or inventory and deal with shipping. There are no startup costs involved. Here is the Flow of Dropshipping: Find Product on Amazon.com → Relist on Ebay (higher price) → SOLD! → Money Goes To Your Paypal → Purchase Product From Amazon.com → Ship Directly To Customer → Profit $$ Simply go to ebay.com and register a free account. Find products on other low cost sites such as Walmart.com & Amazon.com just to name a couple... take the listing from that site and re-post on to ebay at a higher price. Make sure you cover the actual cost of the product on the other site, the 17% ebay/paypal fees and also shipping plus still have room left over for profit! Key To Success:​ Make sure your title has all the keywords that people would be searching for online to find your products! Once you get items ...

 Now you can also purchase PRIVATE LABEL PRODUCTS​ where someone else has written the content and you have the rights to repackage it with your name or brand But... How easy is that? You don’t even have to- write it yourself if you use a private label product. PLR PRODUCTS​ can be found in a variety places. Simply Google PLR products and a ton will come up! You can also purchase them in bulk. Just make sure its quality content before you put your name on it! I personally have not used this site but it has been recommended it to me: PLRMiniMart.com If you’re creating your own ebooks or you’re repackaging PLR​ products... you want to include links to AFFILIATE PRODUCTS​ you promote or that will help add to the information you are sharing. By including links to affiliate products, you are increasing your earning potential plus helping your customer get the best products to assist them in their goals. When it comes to PACKAGING YOUR EBOOK​ , a good place to work through your content is...

 Affiliate marketing is one of my favorite and most profitable ways to earn online. A lot of newbies struggle to earn with affiliate marketing, but I’m here to assure you there is a ton of money to be made with it and you are in the right place to learn it! **Above is a photo of an $18,342.05 month that helped me pay off my BMW in cash! And also a photo of a $336.82 day in just one of my affiliate accounts. First and foremost you want to Pick A Profitable Niche. I personally work with the ‘make money online’ niche and it is by far one of the most profitable. Other great NICHES​ are health & fitness, beauty makeup & cosmetics, self help & personal development. Once you have decided on your niche... it’s time to create some quality content​ ! By giving away information you will be able to build an audience, a group of buyers, loyal followers and become known as a trusted advisor in the niche. I will get more into ways to profit with affiliate marketing as we move through ...

 When considering the future of content marketing, one aspect is of par- ticular significance that nobody who wishes to be successful in the long run should neglect: AI and bots will become game changers in a few years. Many of the former content strategies will be turned upside down by the new pos- sibilities and thus become a greater challenge to companies. Some experts thus speak of the death of the (former) content marketing by the AI algo- rithms. This is certainly an exaggeration, even if provided with a spark of truth. Content marketing itself is regarded as one of the most cost-effective mar- keting strategies that is asserting itself increasingly more worldwide. Even if it is not always easy to be visible on the Internet with one’s own content, one thing remains certain: Customers have a great need for information and want to be entertained. Despite the content shock, the best and most unique contents will always assert themselves somehow. If the demands on content change,...

 There has been a huge hype about chat bots since 2016. Every content officer should take it very seriously. These bots can have a radical effect on content marketing. If we were to receive all contents via an interface like Facebook Messenger, WeChat or Telegram that was previously only available via browsers, newsletters and apps, a thrilling alternative for content distribution would be formed. After all, bots can provide us with relevant information in the right context in the future. Ideally, we will receive less and better information this way and thus avert the content shock. Most bots are simply answering machines that are similar to a living FAQ list or a newsletter. Only a few of them count among the league of AI. If we ask a bot a closed question, we will first receive a simple answer without any surprises. In most cases, bots cannot respond to spontaneous human behaviour and open questions. Instead, we receive a counter question along the lines of: “I don’t know what yo...

 The fear here is that the journalist’s job is disappearing completely. However, AI can also be very helpful in journalism. That should become apparent especially in investigative journalism. Algorithms can help in linking similar information and in extracting individual specifics from general data. The task at hand is to be able to recognise patterns and hypothesise. This is where big data and AI intertwine when, for example, extensive data has to be studied and correlations have to be found. Journalists could then leave the analysis part, which takes up an awful lot of time, to AI and then fully concentrate on writing their article. The point is to implement AI at the right places in a profitable way, not to simply replace the journalist. In addition, AI systems first have to learn The point is to implement AI at the right places in a profitable way, not to simply replace the journalist. In addition, AI systems first have to learn ethical standards. This was demonstrated, for exa...

 It would be conceivable, among others, for AI to adapt texts that have already been created to the linguistic habits of different target groups, so that a medical text, for example, could be understood by both doctors and ordinary people by having medical terms explained. It is merely a question of time until algorithms are able to write texts for any target group whatsoever. In the future, AI will presumably even be able to produce excellent content at an enormous speed. This way, texts can be individualised and personalised more easily so that all essential information is included via a reader and which affects the written and adapted text. AI becomes very familiar with the readership in this process and can uti- lise all information about the recipient in such a way that every single piece of content is unique. Just imagine the content that would be produced if AI could read out your entire (public) Facebook profile and were able to use this information for matching content. In...

 Algorithms are able to automatically search the Web for information, pool it and create a readable piece of writing. In addition, data-based reports in the area of sport, the weather or finances are already frequently created automat- ically today. Recently, for example, merely a few minutes after Apple had announced their latest quarterly figures, there was a report by the news agency Associated Press (AP): “Apple tops Street 1Q forecasts”. The financial report deals solely with the mere financial figures, without any human assistance whatsoever. Yet, AP was able to publish their report entirely via AI in line with the AP guidelines. For this purpose, AP launched their corresponding platform Wordsmith at the beginning of 2016, which automatically creates more than 3000 of such financial reports every quarter, and which are pub- lished fast and accurately. It is no longer that easy to distinguish between whether an algorithm or a human has written a text. Another exception of rece...

  The subject of AI has become increasingly popular in companies ever since the beginning of 2017. It is co-responsible for the search results on Google or Bing. In addition, some of our digital assistants on our smartphone as well as some messenger bots are based on (simple) AI. At the end of 2015, Google extended its algorithm by AI: Google RankBrain. Behind it is a system that learns little by little more about the semantics of user queries and which increasingly improves with this knowledge. The aim: RankBrain is meant to fulfil the users’ needs in an increasingly better way. And with it, Google has taken the first step towards self-learning algorithms. Many upgrades will be possible in the future with- out any human assistance, because the systems will learn something new all on their own. AI will also play a significant role in content marketing when it comes to combining contents with each other and promoting them. What still sounds like dreams of the future will be totally ...

 Relevance and Potential of Bots for Customer  Obtaining information, flight check-ins or keeping a diary of one’s own diet—all of this is possible in dialogue today. Customers can ask questions via Messenger or WhatsApp or initiate processes. This service is comfortable for the customer, available at all times via mobile and promises fast answers or smooth problem-solving. A meanwhile strongly increasing number of companies is already relying on this means of contact and the figures on chat usage speak in favour of this means supplementing or even replacing many apps and web offers in the future. The reasons for this are manifold. Figures of the online magazine Business Insider 1 reveal a clear develop- ment away from the public post to the use of private messaging services such as Facebook Messenger or WhatsApp. Facebook meanwhile has a user base of around 1.7 billion people worldwide; 1.1 billion people use WhatsApp, and Twitter can nevertheless still record 310 million us...

  The algorithm gradient boosted regression trees, also called random forests, belong to the ensemble learning methods This classifier uses an ensemble of weak regression trees that have a low hit quota when considered in isola- tion. The quality of the prediction can be improved significantly when vari- ous trees are trained with different parameters or samples. The results of the individual trees are aggregated to a total result which then enables a more balanced and high-quality prediction. The so-called bagging triggered a boom of the traditional regression trees. As aggregation, either a majority vote or a probability function is chosen (Fig. 5.5). The lead prediction generates high-conversion leads because • The entire spectrum of information available about a company is inte- grated into the decision-making; • The data is highly topical and without bias; • The random forest is capable of abstracting complex correlations in the data; and • The method learns iteratively from t...

 Deep learning is a subject that is causing quite a stir at the moment. In prin- ciple, it is a branch of machine learning that uses algorithms to recognise objects, for example, and understand human speech. The technology is in principle a revival of algorithms, that were popular from the beginnings of AI: Neuronal networks. Neuronal networks are a simulation of the processes in the brain whereby neurons and the specific fire patterns are imitated. The real innovation is the layering of various neuronal networks which, in com- bination with the essentially greater performance of current computers, led to a quantum leap in diverse sectors of machine learning. The classifier for the prediction learns a generic DNA on the basis of pro- filing the successful customer relations, which is projected onto the entire company’s assets. The prediction of the optima leads can be understood as a ranking problem. The lead with the highest probability of a conversion should be in first place in ...

 Sales and Marketing 2017 “Data is the new oil” is a saying that is readily quoted today. Although this sentence still describes the current development well, it ides not get down to the real core of the matter; more suitable would be “artificial intelligence empowers a new economy”. The autonomous automation of ever larger fields of tasks in the business world will trigger fundamental economic and social changes. Based on a future world in which unlimited information is available on unlimited computers, ultimate decisions will be generated in real time and processes will be controlled objectively. These decisions are not liable to any subjectivity, information or delays. In many sectors of the economy, e.g. the public health sector or the autonomous control of vehicles, techniques of artificial intelligence (AI) are applied and increase the quality, availability and integrity of the services offered. The same development can be observed in the field of sales and marketing. Today, ...

 Roadmap for Conversational AI Owing to the technological development and changes in the customer behaviour, e-commerce has developed over different levels of maturity in recent years. The challenge for companies is to recognise relevant technological and market trends and assess them accordingly.  Companies are currently facing the challenge of achieving the next level of maturity—so-called Conversational Commerce. This level of maturity seems desirable at present because current trends could revolutionise the sales sector. This means that those who proceed slowly with the implementation of Conversational Commerce could lose customers to competitors. On the other hand, companies could, for example, benefit from public attention by incorporating bots at an early stage (Fig. 4.8). Thereby, the leap to Conversational Commerce does not represent a gradual, but a fundamental advancement of e-commerce. This is not only about another voice-controlled touch point. It is much rather ...

 Maturity Model The possibilities of implementation of bots are as diversified as the needs of the business and its customers. For a better overview, for degrees of maturity of chatbots can be differentiated The first and lowest level is represented by chatbots without any access whatsoever to other data. Many bots that have been established in customer service until now can be categorised on this level. They secure basic communication, pick up the customer for the time being but soon reach their limits  and pass the customer on to the next touchpoint. On the second level, context information about the consumers is already used. For the duration of the interactions, the bot remembers. thcustomer’s location or the products viewed in the shop and can make recommendations based on this. It is highly situational communication that offers a lot of potential for the customer journey, yet is not aimed at strong customer retention and an empathetic appearance of the system. The next a...

 In 2016, there was a really unusual development of a chatbot: A memorial bot for a deceased friend. Eugene Kuyna, a bot developer of Russian descent from Silicon Valley, got the idea after receiving the devastating news about the casualty Roman Mazurenko. In defiance of all her ethical reservations, she collected thousands of lines of chats from other relatives and fed them into a neural network similar to how Amazon’s Alexa or Apple’s Siri were developed. The results are both fascinating and scary. Many of Mazurenko’s friends that spoke to the bot were staggered at the unique expression of Mazurenko’s, which his bot had perfectly imitated in many places, Even his humour shines through at times. A friend once wrote to him, for example: “You are a genius!” and the bot replied quick-wittedly as Mazurenko would have: “And good-looking!” Kuyna collected some log files of the chats in order to be able to get an idea of the outcome. She noticed that the bot listened more than it spoke. ...