what is deep learningbefore deep learninga brief history of machine learning deep learning has reached level of public attention and industry investment never before seen in the history of aibut it isn' the first successful form of machine learning it' safe to say that most of the machine-learning algorithms used in the industry today aren' deep-learning algorithms deep learning isn' always the right tool for the job--sometimes there isn' enough data for deep learning to be applicableand sometimes the problem is better solved by different algorithm if deep learning is your first contact with machine learningthen you may find yourself in situation where all you have is the deep-learning hammerand every machine-learning problem starts to look like nail the only way not to fall into this trap is to be familiar with other approaches and practice them when appropriate detailed discussion of classical machine-learning approaches is outside of the scope of this bookbut we'll briefly go over them and describe the historical context in which they were developed this will allow us to place deep learning in the broader context of machine learning and better understand where deep learning comes from and why it matters probabilistic modeling probabilistic modeling is the application of the principles of statistics to data analysis it was one of the earliest forms of machine learningand it' still widely used to this day one of the best-known algorithms in this category is the naive bayes algorithm naive bayes is type of machine-learning classifier based on applying bayestheorem while assuming that the features in the input data are all independent ( strongor "naiveassumptionwhich is where the name comes fromthis form of data analysis predates computers and was applied by hand decades before its first computer implementation (most likely dating back to the sbayestheorem and the foundations of statistics date back to the eighteenth centuryand these are all you need to start using naive bayes classifiers closely related model is the logistic regression (logreg for short)which is sometimes considered to be the "hello worldof modern machine learning don' be misled by its name--logreg is classification algorithm rather than regression algorithm much like naive bayeslogreg predates computing by long timeyet it' still useful to this daythanks to its simple and versatile nature it' often the first thing data scientist will try on dataset to get feel for the classification task at hand early neural networks early iterations of neural networks have been completely supplanted by the modern variants covered in these pagesbut it' helpful to be aware of how deep learning originated although the core ideas of neural networks were investigated in toy forms as early as the sthe approach took decades to get started for long timethe missing piece was an efficient way to train large neural networks this changed in the mid- slicensed to