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Cover image for A Guide to Start In Data Science Field.
Razia
Razia

Posted on • Updated on

A Guide to Start In Data Science Field.

Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data.

It's a new Oil to New world, We will discuss here how to start in DS/ML filed.

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Step 1: Choose A programming language

Python and R both are good languages to start your Data science career. R tends to be more popular in academia, and Python tends to be more popular in the industry, but both of language a lot of package t easy your work

Step 2: Learn data analysis, manipulation, and visualization with pandas

Data analysis, manipulation and visualization is an important part of Data science project. As you know the Data more, you will predict it better.

Libraries to learn In python for Data-Analysis

  • Numpy
  • Pandas
  • Matplotlib
  • Seaborn

Step 3: Learn machine learning with scikit-learn

Scikit-learn is a machine learning library. To get start DS/ML. You have to learn it.
It has a lot of supervised and unsupervised implemented in Package and it's an open-source tool. Check more at https://scikit-learn.org/

Step 4: Practice More and More.

Data Science and Machine learning is a growing field, you will face new technology and different problem approach every time. To solve the Data science problem you have to Practice a lot.

Resources for Data Science and Machine learning

Books Recommendation to start

  • The element of statistical learning
  • Hand's on Machine learning with Scikit learn, Keras and TensorFlow
  • Understanding Machine learning Theory Deep learning with Pytorch
  • Machine learning mastery with Python Python For Data analysis

For more details Download Telegram app and visit https://t.me/machinelearningworld

Libraries of Learn Data science

  • Numpy
  • Pandas
  • Matplotlib
  • Seaborn
  • Tensorflow
  • Keras
  • PyTorch
  • Scikit-Learn
  • XGBoost
  • PlotLy

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