Brabu

Problem solving

[Brabu @BRABU45]

Day 1⃣00 #100DaysOfCode

Solved #leetcode Q's:
✅Triangular Sum of an array
✅Duplicate Zeros
✅Sum of Digits of String after Conversion
✅Special position in Binary Matrix

Today highest streak ever:5🌟

Thank you to all my tech companions on this truly enriching journey❤️

[Brabu @BRABU45]

@Palak3312 C

[Brabu @BRABU45]

don't fake data

don't delete data

mean imputation is very danger- like copy paste
guessing the na value using a regression model is also like faking

making randomness also not a good way

and the way I've filling missing data now slightly changed
day 9 of #ML
#stefvanbuuren

[Brabu @BRABU45]

@getajobprachi Atb Prachi!

[Brabu @BRABU45]

Suggest me any ML competitions platforms apart from kaggle.

[Brabu @BRABU45]

@suparnojit26 bro how you l'll handle missing values? apart from mean median mode, if MCAR ,MAr, mnar then for is which approach you will follow?

[Brabu @BRABU45]

Day 8 of ML:

So I'm nt going to move without finding alternate solutions to fill the missing values ♥ ,
So till I've found ppl ar clasiying among MCAR, MAR and MNAR.

👉https://t.co/rrpSPllY23

Leave your thoughts 💭 comment below for better approach!

[Brabu @BRABU45]

@kunalstwt Yyyyyyyy

[Brabu @BRABU45]

Day #sEvAn of ML:

No way i need to find a way, how to classify my missing data to MCAR[Safe], MAR[Cat on the wall] or MNAR[danger]

After draining I've went with @stefvanbuuren book and it's going good..

#Consistency🦾

[Brabu @BRABU45]

Continuation: Or they will use Linear regression data imputer or MICE, we will explore more on this..

[Brabu @BRABU45]

Day 6 of Learning ML:
After completing with Linear regression today went with finding when to use which algo:
and read some @Google ds interview q's there they will 1st classify the NA values into which type
MCAR or MAR or MNAR and then from that if data set is less than 50k KNN

[Brabu @BRABU45]

Day 5 of ML:

All the way went with making the Linear regression imputation and published my blog on medium
check out-https://t.co/Ml26cKE0fz

#ML

[Brabu @BRABU45]

I just published Difference between KNN and Linear Regression data imputer https://t.co/JVqpLmwZxi

[Brabu @BRABU45]

@omarvvvr How your are getting imp??

[Brabu @BRABU45]

Hello @grok ,

I'm looking to connect with people interested in 👀!! 💻 Software Development
🔍 Data Science
🌍 Open Source
✨ SaaS
📢 Building in Public

Let's connect 🤝

[Brabu @BRABU45]

Day 4 of #Learning ML:
Goal is to predict the missing values using linear regression imputer,
IterativeImputer(estimator=LinearRegression(), max_iter=70), this max_iterator we need to set based on the size of the data set.
It is simply tells how many iteration should go!

[Brabu @BRABU45]

Day 3 of Learning #ML:

Started with Random Forest algo high lvl then as linear regression also an way to missing data imputer then I've went with LR approach.

#Goal to make the model to predict the most accurate solution..

[Brabu @BRABU45]

Day 2 of Learning #ML:

Random #forest algo, like the name the topic connect multiple trees to make a prediction or to fill a missing value,
we can specify the number of features to choose not which feature, it is picked dynamically for each iteration.

Trees -> Nodes

[Brabu @BRABU45]

@codewithsushi Nice initiative, can i join?

[Shrushti Raut @codewithsushi]

Hear me out…

Two years back I joined X because I was tired….

Tired of jobs being posted on LinkedIn and within 1 hour of that, 100s of people had already applied. Everyone on LinkedIn was fake, trying to show how they were well-rounded and highly skilled. I barely made any REAL connections there.

Tired of tech influencers on Instagram saying, “COMMENT HI AND I WILL SEND YOU THIS IN YOUR DM,” just to increase their reach. I kept following them, commenting on their reels, getting the material in my DMs, and never really looking at it.

Then there was the cold email era where you send out 1000s of cold emails to recruiters, startup founders, and people in tech to either get a job or get some assistance for your startup. But let’s be honest, out of those 1000 emails, only 10–15 people (max) would reply.

But then there was X, where everyone is just being themselves. Even the most skilled people in your domain feel reachable here. Yes, there are a lot of shitposters, but there are also people who are really, really working hard and building something.

Hence, @shrav_10 and I are creating an X Chat for everyone interested in STARTUPS or TECH, where there will be only REAL tech talk.

We all can post important resources, job openings, and literally even collaborate and discuss startup ideas.

If you’re willing to actually GROW and NETWORK with the right kind of people here on X, then comment/quote/repost anything on this post and I’ll add you to the group chat.

Like I said, the right guidance and network can change your life forever!

[Brabu @BRABU45]

Day 1 of Learning #ML:

KNN(K-Nearest neighbour) Algo:
It will fill the missing value for the given neighbour count take the mean and fill it.
So while pre processing the data itself we can fit & transform(learn from the data) and while test we can just fit and check the results