nayan888 / Learning-and-Experimenting_Data-Science

Journey through data analysis

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Summery

Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data.
Then, what is Data ?
Data is a collection of facts, such as numbers, words, measurements, observations or just descriptions of things.

This repository contains beginner level topics of Machine Learning and Data Science, as well as some advanced topics. It also contain some great projects which I learn. It takes almost four moths to learn all of the basic things for me. This repository is very close to my heart🖤. I have learnt most of the things from Codebasics and some of them from different sources. Hats off to the man of this youtube channel for making this possible. He is awesome teacher! One of the interesting part of his lesson is, he gave exercises for every topic. Please, visit his youtube channel and appreciate his hard work. Note that, I am updating this repository on a regular basis. I highly recommened your contribution and obviously feedback.

Objectives 👼🏼

  • Readable codes which anyone can use as ebook for his learning purpose
  • To recall my memories when I get stuck

Pre-requisite 🗝

  • Python Basic
  • Basic Math ( Calculus, Matrix calculation, Algebra, Statistics)

Where to start 🤔

  1. Pandas
  2. NumPy
  3. Matplotlib & Seaborn
  4. Feature Engineering
  5. Machine Learning
  6. Projects
  7. Deep Learning
  8. ML A-Z
  9. SQL

Set-up Environment 💻

Most of the code executed in jupyter notebook. You can download Anaconda which come up with all necessery packages. Download Anaconda here.
If you're using Jupyter Notebook without anaconda distribution, execute following command. It will install all packages you need right now. 👇🏼

pip install numpy pandas seaborn matplotlib scikit-learn

That's it! Now open your jupyter notebook and Start playing with codes. Good Luck.🤗

What is next🎯

After learning all of the things in this repo, you will be confident enough to do great things. Some of the recommendation what I am doing after this:

  • Doing projects
  • Data Science micro course Kaggle
  • Intro to Inferential Statistics
  • Intro to Descriptive Statistics
  • Data Wrangling
  • SQL for Data Analysis
  • Business Intelligence
  • Tableau/Power BI

Some Great Resources

Youtube:

Websites:

Please, keep in mind that data science is a never end learning process. Prepare yourself for challenging and learning new stuffs regularly.


For Bengali community:
Data Science using Python
যখনি নতুন কিছু শিখেছি, নিজের মতো করে নোট করে রেখেছি। মূলত, সেভাবেই তৈরি হয়েছে এই গিটহাব রিপোসিটরি। আমার মতো যারা ডাটা নিয়ে কাজ করতে আগ্রহী, তাদের কোন কাজ এ লাগতে পারে। নোটবুকে থিউরি ব্যাখ্যা করা আছে, পাশাপাশি কমেন্ট রেখে কোড রিডেবল রাখার চেষ্টা করেছি। কোনটা শুরু করব, কোথায় শুরু করব, রিসোর্স কোথায় পাব এগুলোতে সময় নষ্ট কমিয়ে শেখা শুরু করতে পারবে যে কেউ। ই-বুক এর মতো ব্যবহার করতে পারেন। আমার উদ্দেশ্য ছিলো ২টা।
১| ভবিষ্যতে নিজে কোথাও আটকে গেলে যেন এখান থেকে সাহায্য নিতে পারি।
২| আমি ওপেন সোর্স কমিউনিটি থেকে শিখতেছি। এই কমিউনিটিতে যতটা সম্ভব কন্ট্রিবিউশন করা।
অনুগ্রহ করে রিভিউ/ফিডব্যাক দিবেন 🙏
ধন্যবাদ 🖤

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Journey through data analysis


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