What skills should you start learning to become a data scientist?

I've had a lot of people ask me that recently, but it's really the wrong question.

Try this instead -

➡️ 1. Choose a problem (and dataset) that you find interesting
➡️ 2. Begin trying to solve the problem
➡️ 3. When you get stuck because your skill set is limited, go learn that skill

For example, if you get stuck...
- loading the data into a dataframe/table, then learn pandas or SQL
- identifying outliers, then study stats
- figuring out what to do with missing data, then learn when to remove data, replace values, impute values, etc
- building a regression model that makes good predictions, then learn about regression techniques

👉 There are 2 big differences when you take this approach:

1. You don't waste time guessing what you need to know
2. You're highly motivated to learn at every step of the way

This eliminates the scenario where you're learning a subject because someone else told you it's a good idea.

👉 Now you're learning because you NEED that knowledge for something useful.

Start using this approach in your studies and you'll also see that you're learning more quickly and completely.

#datascience #aspiring #datascientist

✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv

“If you only read the books that everyone else is reading, you can only think what everyone else is thinking.”

Every person has their own way of learning. What helped me break into data science was books. There is nothing like opening your mind to a world of knowledge condensed into a few hundred pages. There is a magic and allure to books that I have never found in any other medium of learning.

There are hundreds of books out there about data science. How do you choose where to start? Which books are ideal for learning a certain technique or domain? While there’s no one-shoe-fits-all answer to this, I have done my best to cut down the list to these 27 books we’ll see shortly.

I have divided the books into different domains to make things easier for you:

1. Books on Statistics
2. Books on Probability
3. Books on Machine Learning
4. Books on Deep Learning
5. Books on Natural Language Processing (NLP)
6. Books on Computer Vision
7. Books on Artificial Intelligence
8. Books on Tools/Languages
- Python
- R

Link : https://bit.ly/2IOPV8T

#python #books #artificialintelligence #datascience
#machinelearning #statistics #datascientist #deeplearning

✴️ @AI_Python_EN

How This Researcher Is Using #DeepLearning To Shut Down Trolls And Fake Reviews. #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #PyTorch #Python #RStats #JavaScript #ReactJS #GoLang #Serverless #DataScientist #Linux

🌎 https://bit.ly/2U2J5BX

✴️ @AI_Python_EN

The life of a #DataScientist...
✴️ @AI_Python_EN

I wanna be a data scientist, but… how!?

https://link.medium.com/CUDoPvMOEV
#DataScience #ArtificialIntelligence #MachineLearning #DeepLearning #DataScientist


✴️ @AI_Python_EN

The ability to deal with imbalanced datasets is a must-have for any #datascientist. Here are 4 tutorials to learn the different techniques of handling imbalanced data:

How to handle Imbalanced #Classification Problems in #MachineLearning? - https://buff.ly/2sIsR0M

Investigation on Handling Structured & Imbalanced Datasets with #DeepLearning - https://buff.ly/2MpxuG1

This Machine Learning Project on Imbalanced Data Can Add Value to Your #DataScience #Resume - https://buff.ly/2Mpr2i0

Practical Guide to deal with Imbalanced Classification Problems in #R - https://buff.ly/2MrS8Fr

✴️ @AI_Python_EN

DeepAMD: Detect Early Age-Related Macular Degeneration.
#BigData #Analytics #DataScience #AI #MachineLearning #DeepLearning #IoT #IIoT #PyTorch #Python #CloudComputing #DataScientist #Linux
https://link.springer.com/chapter/10.1007%2F978-3-030-20873-8_40

✴️ @AI_Python_EN

One of the BEST #MachineLearning Glossary by Google

It will definitely come in handy - https://lnkd.in/gNiE9JT

Link to learn more about Machine Learning:

✅ Course 1 : A comprehensive Learning Path to become Data Scientist in 2019
Link : https://bit.ly/2HOthei

✅ Course 2 : Experiments with Data
Link : https://bit.ly/2HQuQbw

✅ Course 3 : Python for Data Science
Link : https://bit.ly/2HOG5RG

✅ Course 4 : Twitter Sentiments Analysis
Link : https://bit.ly/2HR8O8A

✅ Course 5 : Creating Time Series Forecast with Python
Link : https://bit.ly/2XniU6r

✅ Course 6 : A comprehensive path for learning Deep Learning in 2019
Link : https://bit.ly/2HO1VVJ

✅ Course 7 : Loan Prediction Practice problem
Link : https://bit.ly/2IcynQl

✅ Course 8 : Big mart Sales Problem using R
Link : https://bit.ly/2JUlZIb

#announcements #datascientist #machinelearning #datascience #artificialintelligence

✴️ @AI_Python_EN

Getting System Information in Linux using Python Script.
#BigData #Analytics #DataScience #IoT #PyTorch #Python #RStats #TensorFlow #DataScientist #Linux

http://bit.ly/2X56cZa

✴️ @AI_Python_EN

Here is an exclusive video that highlights the 5 things that any aspirant should consider before choosing a Machine Learning course. Watch the full video here:
https://lnkd.in/fVyW5Uq



#machinelearning #artificialintelligence #datascience #deeplearning #datascientist #ai

✴️ @AI_Python_EN

Pytorch Implementation of Deep Flow.

#BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #TensorFlow #CloudComputing #DataScientist #Linux

https://arxiv.org/pdf/1905.02884.pdf

✴️ @AI_Python_EN

ANNOUNCING PYCARET 1.0.0 - An amazingly simple, fast and efficient way to do machine learning in Python. NEW OPEN SOURCE ML LIBRARY If you are a DATA SCIENTIST or want to become one, then this is for YOU....

PyCaret is a NEW open source machine learning library to train and deploy ML models in low-code environment.

It allows you to go from preparing data to deploying a model within SECONDS.

PyCaret is designed to reduce time and efforts spent in coding ML experiments. It automates the following:

- Preprocessing (Data Preparation, Feature Engineering and Feature Selection)
- Model Selection (over 60 ready-to-use algorithms)
- Model Evaluation (50+ analysis plots)
- Model Deployment
- ML Integration and Monitoring (Power BI, Tableau, Alteryx, KNIME and more)
- ..... and much more!

Watch this 1 minute video to see how PyCaret can help you in your next machine learning project.

The easiest way to install pycaret is using pip. Just type "pip install pycaret" into your notebook.

To learn more about PyCaret, please visit the official website https://www.pycaret.org

#datascience #datascientist #machinelearning #ml #ai #artificialintelligence #analytics #pycaret

❇️ @AI_Python_EN