In every skill, there are some rules or said to be a hierarchy. It means you would not be able to read even a single word if you have not understood the alphabet. You cannot understand the meaning of a single sentence If no idea of how the syntax of specific language work.
Deep learning is a subset of AI (Artificial Intelligence) & ML (Machine Learning), and you will have to understand the basics. The basics of machine learning play a vital role in your understanding like supervised, and unsupervised learning, and many more. You can join free courses or book reading habits for core concepts learning.
A human brain can learn new things through reading blogs, writing new techniues algorithms, and watching content on youtube.
Before jumping to data science, the prerequistcs are strong concepts of object oriented programming language like c++ java, python etc.
Most of the people recommend to learn machine learning – because they claim that most of the concepts are same.
Most of the data science experts recomed to learn machine learning first. As you know the technology has created the easy ways for us to learn fast.
Following Tips You Can Learn Deep Learning Without Machine Learning:
3.Basic Maths
How the algoritjhms of ML work to perform, what will be the output and do you know structure of it? Not enough to think it a blackbox where you put the input and get output from the other side. To develop your own solution, tou should know the internal working or mechnisam which is full of mathematics and statistics.
Take deep concepts and of linear algebra, statistics, and calculus to go dive into algorithms. You can develop your own algorithms through deep understandings what is going on in current in the market.
There is a long list of algorithms for speech recognition, text processing, image processing and stock exchange analysis.
Following books will be useful for getting mathematics concepts:
- Linear algebra by Gilbert Strang
- Harvard stats 110 by Joe
These books/ materials might help you to get deeper and deeper to take the working of algorithsm. It wiill be the start of your carrer as data scientist.
2.Programming Language
You are excited to learn data science , right, there are lost of languages that are good in the market. Deep learning is the most powerful for prediciton and analysis, c++ also called mother language.
A survery of data science market tell that leading language for analysis is python. 33% developers reccommend it and almsot 60% of developers it for development.
Python is also compred with R langauge and c++ is the second most used langauge for data analysis. All the languages are state-of-the-art in their era. So which programming language would you love ot choose and why? Comment it.
1.Reading Blogs
Blogs tell you important updates, new tecnniques, datasets and many more what is going in the market. So make daily habits to read and learn a small piece of information as a career in data science. So. most of the three most important and accurate blogs are twowardsdatascience, OpenAI and machinelearningisfun.
BottomLine
You can directly jump to deep learning and you need only consistency. Solve mathematics probelm, complete mini assignments and go through a tough training process, you will become a hero data scientist. Reading is going to be your favorite tool, reason behind is a lot of concepts you will learn through blogs. Join free platform for learning basics of any programming language.