Starting introduction of Data Science

Data science is a vast area. It’s actually related to every sector and every domain. Before knowing the starting introduction of data science we need to know one thing. In the most simple way, Data science is a sector where we will get the part of

1. Computer science

2. Machine learning

3. Deep learning

4. Artificial intelligence

So, we could say every part is in Data science but not all is data science. We will discuss ML, DL, and AI but apart from the side of computer science, there is a strong need for data structure, database, and programming language knowledge. Sometimes obviously operating systems are there.

Artificial Intelligence

Artificial intelligence is the science and engineering of making such a machine which performs tasks and works like humans. The three parts are: the first is Artificial narrow intelligence, the second is Artificial general intelligence, and the third is Artificial super intelligence. AI demands are computational power, data, algorithm, and broad investment. The first type of AI we right are using, the second one is just a type of human, and the third one is like the movie Matrix. AI is usually a process which is made by machine learning techniques.

Machine learning

Machine learning is a computer program which focuses on the designing of systems and allowing them to run and make predictions based on experience. It is the subset of AI.

It has three types 1. Supervised, 2. Unsupervised, 3. Reinforcement learning.

The machine learning process steps are 1. Define the objective, 2. Data gathering, 3. Preparing, 4. Exploration, 5. Building model, 6. Evaluation, 7. Prediction

The problems which we solve are Regression, classification, association, clustering, reward

All types of data we gather and process according to the type of ML

Similarly, the algorithm we use is LR, Logistic regression, SVM, KNN, K-means, Q-learning etc.

(For more see the machine learning blog)

Deep learning

It is the manual steps of extracting features for making predictions. Deep learning works according to the neuron of the brain. collecting the data processing it and predicting that and sending that to another. In this case, the artificial neuron is another thing which separates the data and predictions.

Deep learning frameworks are Tensorflow, Pytorch, Mxnet, CNTK etc. These help to gather the data, then process those and then predict them.

Obviously, the ML algorithm applies too for the processing

(For more see the Deep learning blog)

This is a simple introduction to data science for starting or entering this sector. The must-needed knowledge is 1. data structure, 2. one programing language, 3. Database, 4. Math, 5. Statistics