Machine Reading systems are developed to produce language-understanding technology that will automatically process text in affordable time. In this tutorial the idea of automatically reading the Web using Machine Reading techniques will be explored. Four of the most successful Machine Reading approaches intended to Read the Web (namely DBPedia, Yago, OIE (Open Information Extraction) and NELL projects) will be presented and discussed. The principles, the subtleties, as well as current results of each approach will be addressed. On-line resources (from each approach) will be explored and the future directions in each project will be pointed out. DBPedia, YAGO, OIE and NELL are not the only research efforts focusing on “Reading the Web”. They were selected, to be presented in this tutorial, because they show different and very relevant approaches to this problem, but it does not mean they are the only relevant approaches at all. In spite of mainly focusing on the four aforementioned projects, some other independent contributions, on the Read the Web idea, will be mentioned and pointed out as related works. In addition, two other industrial projects, namely Google Knowledge Vault and IBM Watson will also be explored in a more summarized approach.