Spam email watch How to protect yourself from spam emails

What is a spam (junk mail) offer?

Spam is an unsolicited (or junk) email. Spam emails usually offer free goods or ‘prizes’, very cheap products (including pharmaceuticals), promises of wealth or other offers that could result in you taking part in a scam. You might be asked to pay a joining fee, to buy something to win a prize or some other benefit, or to call a 190 telephone or fax number (calls made to these numbers are charged at premium rates). Spam emails can basically offer you anything and everything—from fake college degrees to pirated software and counterfeit designer watches—so it pays to be suspicious and delete unsolicited emails.

Spam emails differ from regular printed junk mail in one major way—responding to a scam email can cause you many problems. You may find that malicious software like spyware or key-loggers has been downloaded onto your computer. Your credit card or other personal details may be stolen. You may send away money for something that never arrives or is not what you thought it would be.


Warning signs
You receive an unsolicited email that contains:

• an invitation to participate in any type of lottery or sweepstake
• an offer of uninvited gifts or goods from any source
• an offer from overseas
• a request to pay a fee to receive more benefits from the same provider
• an offer from an unregistered lottery
• an offer of special benefits (eg, wealth, love, health) from someone claiming psychic powers
• an offer of a gambling system that guarantees winners.

Protect yourself against spam (junk mail) offers

• Do not open suspicious or unsolicited emails (spam): delete them.
• Do not click on any links in a spam email, or open any files attached to them.
• Never call a telephone number that you see in a spam email.
• NEVER reply to a spam email (even to unsubscribe).
• Never enter your personal, credit card or online account information on a website that you are not certain is genuine.
• Never send your personal, credit card or online account details through an email.
• Use your common sense: the offer may be a scam.
• Read all the terms and conditions of any offer very carefully: claims of free or very cheap offers often have hidden costs.
• Do not send any money or pay any fee to claim a prize or lottery winnings.

Do your homework
Remember that letters, emails and other approaches offering you something that looks too good to be true are almost always scams.

If you are interested in what the email is offering, contact your local office of fair trading to see if they can tell you more about the offer.

If you are interested in an offer, use a search engine to locate the firm’s website address. Be sure that you know what the offer is actually for, what the total cost will be and what to do if something goes wrong (e.g. the product is not delivered or does not work).

Seek independent advice from an accountant or solicitor if a significant amount of money is involved. Don’t provide your credit card or bank account details to ANYBODY you are not completely sure about.


Decide
If you receive a spam offer, the best thing to do is delete the email. Do NOT respond. Do not email back, do not call any telephone number listed in the email and do not send any money, credit card details or other personal details to the scammers. Responding only indicates youre interested and you could end up with lots more fake offers in the future.

If you are interested in what the spam email is offering, it is still best not to follow any link contained in the email. Internet links do not always lead where their name says they do. Sometimes, clicking on a link will download a program to your computer. Make sure you have done your homework before doing anything to take up an offer from a spam email.

Source:- http://www.scamwatch.gov.au/
There is a website dedicated to spam. You can read lots more. Visit

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Teach Yourself Deep Learning with TensorFlow and Udacity

Posted by Vincent Vanhoucke, Principal Research Scientist

Deep learning has become one of the hottest topics in machine learning in recent years. With TensorFlow, the deep learning platform that we recently released as an open-source project, our goal was to bring the capabilities of deep learning to everyone. So far, we are extremely excited by the uptake: more than 4000 users have forked it on GitHub in just a few weeks, and the project has been starred more than 16000 times by enthusiasts around the globe.

To help make deep learning even more accessible to engineers and data scientists at large, we are launching a new Deep Learning Course developed in collaboration with Udacity. This short, intensive course provides you with all the basic tools and vocabulary to get started with deep learning, and walks you through how to use it to address some of the most common machine learning problems. It is also accompanied by interactive TensorFlow notebooks that directly mirror and implement the concepts introduced in the lectures.

The course consists of four lectures which provide a tour of the main building blocks that are used to solve problems ranging from image recognition to text analysis. The first lecture focuses on the basics that will be familiar to those already versed in machine learning: setting up your data and experimental protocol, and training simple classification models. The second lecture builds on these fundamentals to explore how these simple models can be made deeper, and more powerful, and explores all the scalability problems that come with that, in particular regularization and hyperparameter tuning. The third lecture is all about convolutional networks and image recognition. The fourth and final lecture explore models for text and sequences in general, with embeddings and recurrent neural networks. By the end of the course, you will have implemented and trained this variety of models on your own machine and will be ready to transfer that knowledge to solve your own problems!

Our overall goal in designing this course was to provide the machine learning enthusiast a rapid and direct path to solving real and interesting problems with deep learning techniques, and were now very excited to share what weve built! It has been a lot of fun putting together with the fantastic team of experts in online course design and production at Udacity. For more details, see the Udacity blog post, and register for the course. We hope you enjoy it!

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