Machine Learning (known as Multi Variate Analysis) has been used somewhat in HEP since the nighties. If Boosted Decision Trees are now common place, there is now an explosion of novel algorithms following the « deep learning revolution » in industry, applicable to data taking, triggering and handling, reconstruction, simulation and analysis. This talk will review some of these algorithms and their prospects. The number of published physics measurements or applications in production is however still low. We will conclude on the ingredients to facilitate these last steps.