# What Is RoadMap For Deep Learning

Hello, Guys Today we are going to explore the World Of deep Learning and Some Important Aspect of Deep Learning. We Exlpolring, What is the best way to learn Deep Learning in an efficient way (RoadMap)? , Which are the Best Programming languages for Deep Learning? Which are the best Libraries for Deep Learning? Which Project should do on deep Learning ?, So let's Explore.

## Deep Learning

## -Introduction To Deep Learning

Actually, Deep Learning is The Part of Machine Learning. Deep Learning is like Human Brain, Human Brain is always learns something new and analyzes that condition, and properly reacts to that particular situation. Just Human Brain Deep Learning Model, automatically Learn the new case and new information ( data ), To bring best result and Predictions.

The Deep Learning acts like Machine Learning, The only difference bet Machine learning and Deep Learning is that we need to train both models but in the case of deep learning learn the new condition and prepare the output for it but in the case of Machine Learning it cant Happen. Because of Deep Learning in the future, the robots don't need the operator to operate them and passed the command to them, they were learning on their own how to run and run.

The Deep Learning Required Math portion also for Prediction so let's get it.

## -How Much Math Is Required For Deep Learning

The Deep Required the Math portion For Prediction and find the best solution to a given problem. Deep Learning required the math portion of Statistics, Probability, Differential Calculus & graph theory. In Deep Learning, Machine Leaning math is Important while programming and thinking the logic for the solution of a given problem. For Beginners to start Machine learning and Deep learning, Then Start the math First and then Go for any languages and their ML & DL algorithms.

Linear Algebra is used to arrange the data in a specific manner and convert the given data set into an algebraic format that the machine can easily understand.

Differential Calculus is used to calculate the equation and give the total solution of that algebraic equation.

Statistics & Probability are used to analyze the data and predict the output. Basically, Probability means is finding the probability ( prediction ) of some things.

## -Which Programming Language is Best For Deep Learning

In Deep Learning the Best programming Languages are Python, R, Julia, JavaSCript & Lisp, The R and Python Are the best Programming Languages used for DL. Python is widely used for ML, Dl, and normal coding (Problem Solving / Web development). Python Supports many Libraries so that developers can easily implement the ML & Dl model with less effort. Python is an all-rounder language that supports ML & Dl with Web, apps & oops concepts.

## -Which are the Best Libraries For Deep Learning

TensorFlow, Pytorch, Theano & OpenNN are some best Libraries for deep Learning. Among these, the TensorFlow is best Because TensorFlow is used for both Ml & DL. The Numpy is a python library that is used for mathematical operation. Pytorch library is used a facial recognition system. The library is helping to reduce the calculation & code implementation. The Deep learner can easily learn things due to the library. For the Deep learner should learn the important library which is important.

## -Advanced Deep Learning

To Become a master in Deep Learning then learn math Firstly and then learn any language which supports Deep Leaning with learn the Data Structure and OOPs Concepts. after that Learn the Important Libraries like TensorFlow, PyTorch and others. After You Completing all stuff of Deep Learning, Try To implement the thing and develop the models of your ideas. Try to make a model ( Projects ) such as Predtiton, Images Classification, Face Detection, Facial Expression,

## Conclusion

The Deep Learning Is the Aspect of The Artificial Intelligence and Machine Learning. For The Machine LEarner and AI learner, This is an important concept for developing the AI model. Deep Learning is Also a Concept of Data science. To learn Data Science, we need to learn all stuff regarding Machine Learning, Deep Learning, Artificial Intelligence. Deep Learning consists of many libraries which help to reduce the effort to develop a specific model. Deep Learning is like a human brain, The Human brain is always learning from something like any event that happens in life, The result of that event will get learn and analyzed by the Brain, Just like that Deep Learning, learn automatically from a certain condition. This makes the Robot get their own brain so that they don't need to an operator to operate and pass the command.

## FAQ

## Que 1): What is the mean of Deep Learning?

Ans : Deep Learning is Part Of Machine Learning And Artificial Intelligence, Which Behaves like the human Brain, Which Always consumed and store, analyze new information (data ) , and work on it make the model more precise.

## Que 2): Which Programming Languages Support Deep Learning?

Ans : Python, R, Java, JavaScript, Julia, Lisp, and many more are supporting, these are popular programming Languages that support Deep Learning.

## Que 3): Which Part of Math is Required for Deep Learning?

Ans : Statistics, Probability, Linear Algebra, Differential Calculus, are the main Topics of math used in Deep Learning.

## Que 4): Which are the best Books for Deep Learning?

Ans : Deep Learning With Python by Chollet, Deep Learning by Aaron, are the some of best books for Deep Learning.

## Que 5): Which Are Libraries used for Deep Learning?

Ans: TensorFlow, Pytorch, Theano & OpenNN are some best Libraries for deep Learning.

## Que 6): Which Project can do on Deep Learning?

Ans: Image Classification and audio classification, Neural Network, These are some Project Ideas For Deep Learning.

## Que 7): Which Best Python or R for ML &DL?

Ans: Both Languages are best for ML & DL.

Please Comment on your Query Regarding Machine learning, Deep Learning & Other Python concepts I will try to find the solution if These.