Tweet

Piyal Banik

2 Jul, 9 tweets, 4 min read

Best Data Science blogs to follow in 2021

🧵👇

#DataScience #66daysofdata #100DaysOfCode

1. Towards Data Science

TDS is a Medium publication having audience-oriented content about Data Science, along with blogs on related fields such as Machine Learning, Programming, Visualization, and Artificial Intelligence.

towardsdatascience.com

2. Data Science Central

DSC is one of the leading repositories of Data Science content that is regularly updated with the latest trends across domains such as Artificial Intelligence, Machine Learning, Deep Learning, Analytics, Big Data, and much more.

datasciencecentral.com

3. Data Science Reddit

Reddit is world-renowned news and discussion website with hundreds of diverse communities and millions of active users.

reddit.com/r/datascience/

4. KDnuggets

KDnuggets is a well-known and prestigious site for gaining information about some of the rapidly growing technologies in the world, including Data Science, Artificial Intelligence, Analytics, Machine Learning, Data Mining, and Big Data.

kdnuggets.com

5. Analytics Vidhya

Analytics Vidhya offers a complete Data Science ecosystem through its four vital pillars.

analyticsvidhya.com

6. Data Science | Google News

With Google’s one-stop solution to all your Data Science news, readers can get access to a sea of information, covering every aspect of the topics.

news.google.com/datascience

7. DataCamp

DataCamp is an industry-leading online course provider for Data Science providing hands-on experience with some of the widely used tools in the Data Science industry

datacamp.com

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More from @PiyalBanik

Piyal Banik

@PiyalBanik

3 Jul

Want to learn Data Science but confused about where to start and what to follow?

Here are the ultimate 12 months Learning path to becoming a Data Scientist 👨‍🎓

Note: I'm personally following this roadmap

🧵👇

#DataScience #MachineLearning #100DaysOfCode #66DaysOfCode #Python

Since we're currently in July, so start from this month.

Understanding Data Science and getting started with Python
- what is data science?
- what does a data scientist do?
- find out various resources
- Set up the system
- Learn Python basics
- Introduction to Pandas & Numpy

August -

Mathematics, Statistics & SQL
- Linear Algebra
- Introduction to Probability
- Statistics - inferential & descriptive
- Exploratory Data Analysis
- SQL for Data science
- Projects on EDA and SQL

Start engaging in the Data Science & Machine Learning community

Read 14 tweets

Piyal Banik

@PiyalBanik

3 Jul

Ever wondered how a Data Scientist thinks about a problem? Here are the major steps involved in solving a data science problem.

🧵👇

#DataScience #MachineLearning #100DaysOfCode #66DaysOfData

1. Business Understanding: We should have clarity of what is the exact problem we are going to solve.

What is the problem that we are trying to solve? - Asking the right questions as a Data Scientist starts with understanding the goal of the business.

2. Analytical Approach: How can we use data to answer the question? We should decide the analytical approach to follow which can be of 4 types
- Descriptive
- Statistical
- Predictive
- Prescriptive
and it indicates the necessary data content, formats, and sources to be gathered

Read 12 tweets

Piyal Banik

@PiyalBanik

1 Jul

NumPy 🔥

It is a Linear Algebra Library for #Python, the reason it is so important for Data Science is that almost all of the libraries in the PyData Ecosystem rely on NumPy as one of their main building blocks👨‍🏫.

Here's everything you need🧵👇

#DataScience #100DaysOfCode

1⃣Numpy Arrays

NumPy arrays are the main way we use Numpy. Numpy arrays essentially come in two flavors: vectors and matrices. Vectors are strictly 1-d arrays and matrices are 2-d (but you should note a matrix can still have only one row or one column).

2⃣Built-in Methods

There are lots of built-in ways to generate Arrays
- zeros
- ones
- eye
- arange
- linspace

Read 11 tweets

Piyal Banik

@PiyalBanik

19 Jun

Ever wondered how a Data Scientist thinks about a problem? Here are the major steps involved in tackling a data science problem.

Thread 🧵👇

#DataScience #MachineLearning #100DaysOfCode

Read 12 tweets

Piyal Banik

@PiyalBanik

18 Jun

Top 7 interesting careers related to Data Science to explore. Pick one and start learning.

Thread 🧵👇

#DataScience #ArtificialIntelligence #MachineLearning #BigData

1. Data Scientist

Data scientist use their analytical and technical capabilities to extract meaningful insight from data.

2. Machine Learning Engineer

Machine Learning engineer's final output is the working software, and their audience for this output consists of other software components that run automatically with minimal human supervision. The decisions are made by machines.

Read 9 tweets

Piyal Banik

@PiyalBanik

18 Jun

Everything you need to know about Strings in Python for Data Science

Thread 🧵👇

#DataScience #Python #100daysofcodechallenge

📌Looping Through a String

Since strings are arrays, we can loop through the characters in a string, with a for loop.

📌String Length
To get the length of a string, use the len() function.

📌Check String
To check if a certain phrase or character is present in a string, we can use the keyword in.

Read 8 tweets

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