• Latest
  • Trending
Want to Be a Data Scientist? Don’t Start With Machine Learning

Want to Be a Data Scientist? Don’t Start With Machine Learning

December 30, 2021
Apple releases iOS 15.5 RC, here’s the list of everything new

Apple releases iOS 15.5 RC, here’s the list of everything new

May 13, 2022
MSI Full AMD 300-Series Motherboard Compatibility for Zen 3

MSI Full AMD 300-Series Motherboard Compatibility for Zen 3

May 13, 2022
Gigabyte New Flagship AORUS 17X Gaming Laptop with Extreme Performance

Gigabyte New Flagship AORUS 17X Gaming Laptop with Extreme Performance

May 13, 2022
MediaTek Unveils New AIoT Platform Stack and Genio 1200 AIoT Chip

MediaTek Unveils New AIoT Platform Stack and Genio 1200 AIoT Chip

May 13, 2022
Oracle expands global network of industry innovation labs

Oracle expands global network of industry innovation labs

May 13, 2022
Google announces 30,000 scholarships under African developer scheme

Google announces 30,000 scholarships under African developer scheme

May 13, 2022
Huawei attracts global talent to tackle world-class challenges

Huawei attracts global talent to tackle world-class challenges

May 13, 2022
MTN SA Commits R2.2 Billion For Network Modernisation

MTN SA Commits R2.2 Billion For Network Modernisation

May 13, 2022
Micron Delivers Industry-Leading Capacity Sizes and QLC NAND

Micron Delivers Industry-Leading Capacity Sizes and QLC NAND

May 13, 2022
ADATA LEGEND 850 and Limited Edition PCIe Gen4 x4 M.2 2280 SSDs

ADATA LEGEND 850 and Limited Edition PCIe Gen4 x4 M.2 2280 SSDs

May 13, 2022
SMART Modular Technologies New DuraMemory DDR5 VLP RDIMM

SMART Modular Technologies New DuraMemory DDR5 VLP RDIMM

May 13, 2022
Apacer Announces PV930-M280 SSD Powered by 112-layer BiCS5 Flash

Apacer Announces PV930-M280 SSD Powered by 112-layer BiCS5 Flash

May 13, 2022
  • Consumer Watch
  • Kids Page
  • Directory
  • Events
  • Reviews
Monday, 16 May, 2022
  • Login
itechnewsonline.com
  • Home
  • Tech
  • Africa Tech
  • InfoSEC
  • Data Science
  • Data Storage
  • Business
  • Opinion
Subscription
Advertise
No Result
View All Result
itechnewsonline.com
No Result
View All Result

Want to Be a Data Scientist? Don’t Start With Machine Learning

The biggest misconception aspiring data scientists have

by ITECHNEWS
December 30, 2021
in Data Science, Leading Stories
0 0
0
Want to Be a Data Scientist? Don’t Start With Machine Learning

The first thing most people think about when they hear the term “data science” is usually “machine learning”.

This was the case for me. My interest in data science sparked because I was first exposed to the idea of “machine learning” which sounded really cool. So when I was looking for a place to start learning about data science, you can guess where I started (hint: it rhymes with bean churning).

This was my biggest mistake and this leads me to my main point:

If you want to be a data scientist, don’t start with machine learning.

Bear with me here. Obviously, to be a “complete” data scientist, you’ll have to eventually learn about machine learning concepts. But you’d be surprised at how far you can get without it.

So why shouldn’t you start with machine learning?

1. Machine learning is only one part of a data scientist (and a very small part too).

Image created by Author

Data science and machine learning are like a square and a rectangle. Machine learning is (a part of) data science but data science isn’t necessarily machine learning, similar to how a square is a rectangle but a rectangle isn’t necessarily a square.

In reality, I’d say that machine learning modeling only makes up around 5–10% of a data scientist’s job, where most of one’s time is spent elsewhere, which I’ll elaborate on later.

YOU MAY ALSO LIKE

Apple releases iOS 15.5 RC, here’s the list of everything new

MSI Full AMD 300-Series Motherboard Compatibility for Zen 3

TLDR: By focusing on machine learning first, you’ll be putting in a lot of time and energy, and getting little in return.

2. Fully understanding machine learning requires preliminary knowledge in several other subjects first.

At its core, machine learning is built on statistics, mathematics, and probability. The same way that you first learn about English grammar, figurative language, and so forth to write a good essay, you have to have these building blocks set in stone before you can learn machine learning.

To give some examples:

  • Linear regression, the first “machine learning algorithm” that most bootcamps teach first is really a statistical method.
  • Principal Component Analysis is only possible with the ideas of matrices and eigenvectors (linear algebra)
  • Naive Bayes is a machine learning model that is completely based on Bayes Theorem (probability).

And so, I’ll conclude with two points. One, learning the fundamentals will make learning more advanced topics easier. Two, by learning the fundamentals, you will already have learned several machine learning concepts.

3. Machine learning is not the answer to every data scientist’s problem.

Many data scientists struggle with this, even myself. Similar to my initial point, most data scientists think that “data science” and “machine learning” go hand in hand. And so, when faced with a problem, the very first solution that they consider is a machine learning model.

But not every “data science” problem requires a machine learning model.

In some cases, a simple analysis with Excel or Pandas is more than enough to solve the problem at hand.

In other cases, the problem will be completely unrelated to machine learning. You may be required to clean and manipulate data using scripts, build data pipelines, or create interactive dashboards, all of which do not require machine learning.

What should you do instead?

If you’ve read my article, “How I’d Learn Data Science If I Had to Start Over,” you may have noticed that I suggested learning Mathematics, Statistics, and programming fundamentals. And I still stand by this.

Like I said before, learning the fundamentals will make learning more advanced topics easier, and by learning the fundamentals, you will already have learned several machine learning concepts.

I know it may feel like you’re not progressing to be a “data scientist” if you’re learning statistics, math, or programming fundamentals, but learning these fundamentals will only accelerate your learnings in the future.

You have to learn to walk before you can run.

If you would like some tangible next steps to start with instead, here are a couple:

  1. Start with statistics. Of the three building blocks, I think statistics is the most important. And if you dread statistics, data science probably isn’t for you. I’d check out Georgia Tech’s course called Statistical Methods, or Khan Academy’s video series.
  2. Learn Python and SQL. If you’re more of an R kind of guy, go for it. I’ve personally never worked with R so I have no opinion on it. The better you are at Python and SQL, the easier your life will be when it comes to data collection, manipulation, and implementation. I would also be familiar with Python libraries like Pandas, NumPy, and Scikit-learn. I also recommend that you learn about binary trees, as it serves as the basis for many advanced machine learning algorithms like XGBoost.
  3. Learn linear algebra fundamentals. Linear algebra becomes extremely important when you work with anything related to matrices. This is common in recommendation systems and deep learning applications. If these sound like things that you’ll want to learn about in the future, don’t skip this step.
  4. Learn data manipulation. This makes up at least 50% of a data scientist’s job. More specifically, learn more about feature engineering, exploratory data analysis, and data preparation.
Source: Terence Shin, Data Scientist @ KOHO
Via: Data and Marketing Advisor
Tags: Data ScientistML
ShareTweetShare

Get real time update about this post categories directly on your device, subscribe now.

Unsubscribe

Search

No Result
View All Result

Recent News

Apple releases iOS 15.5 RC, here’s the list of everything new

Apple releases iOS 15.5 RC, here’s the list of everything new

May 13, 2022
MSI Full AMD 300-Series Motherboard Compatibility for Zen 3

MSI Full AMD 300-Series Motherboard Compatibility for Zen 3

May 13, 2022
Gigabyte New Flagship AORUS 17X Gaming Laptop with Extreme Performance

Gigabyte New Flagship AORUS 17X Gaming Laptop with Extreme Performance

May 13, 2022

About What We Do

itechnewsonline.com

We bring you the best Premium Tech News.

Recent News With Image

Apple releases iOS 15.5 RC, here’s the list of everything new

Apple releases iOS 15.5 RC, here’s the list of everything new

May 13, 2022
MSI Full AMD 300-Series Motherboard Compatibility for Zen 3

MSI Full AMD 300-Series Motherboard Compatibility for Zen 3

May 13, 2022

Recent News

  • Apple releases iOS 15.5 RC, here’s the list of everything new May 13, 2022
  • MSI Full AMD 300-Series Motherboard Compatibility for Zen 3 May 13, 2022
  • Gigabyte New Flagship AORUS 17X Gaming Laptop with Extreme Performance May 13, 2022
  • MediaTek Unveils New AIoT Platform Stack and Genio 1200 AIoT Chip May 13, 2022
  • Home
  • InfoSec
  • Opinion
  • Africa Tech
  • Data Storage

© 2021 iTechNewsOnline.Com - Powered by BackUpDataSystems

No Result
View All Result
  • Home
  • Tech
  • Africa Tech
  • InfoSEC
  • Data Science
  • Data Storage
  • Business
  • Opinion

© 2021 iTechNewsOnline.Com - Powered by BackUpDataSystems

Welcome Back!

Login to your account below

Forgotten Password?

Retrieve your password

Please enter your username or email address to reset your password.

Log In

Add New Playlist

Are you sure want to unlock this post?
Unlock left : 0
Are you sure want to cancel subscription?
Go to mobile version