A topic that comes up in every interview.

Bias, variance, and their relationship with machine learning algorithms. One of the most basic concepts that you have to know by heart.

Here is a simple summary that you will easily remember.

↓

I'll blow your mind with a technique you aren't using yet.

Sometimes, you want your system to do exactly the opposite of what your machine learning model thinks you should do.

Let me convince you. ↓

I'm going to start with a nice problem:

Imagine a model that looks at a picture of an electrical transformer and predicts whether it's about to break or not.

Don't worry about how the model does this. We are going to focus on the results instead.

There are 4 possible results for this model:

1. It predicts a bad unit as bad.
2. It predicts a bad unit as good.
3. It predicts a good unit as bad.
4. It predicts a good unit as good.

#2 and #3 are the mistakes the model makes.

Assuming we run 100 units through the model, we can organize the results in a matrix:

• The rows represent the "actual" condition of the transformer.

• The columns represent the "prediction" of the model.

We call this a "Confusion Matrix."

This is how we can read this confusion matrix:

• 60 bad units were predicted as bad.
• 3 bad units were predicted as good.
• 7 good units were predicted as bad.
• 30 good units were predicted as good.

My recommendation to start learning how to deal with structured data: Kaggle's Pandas Tutorial.

• Creating, Reading, Writing
• Indexing, Selecting, Assigning
• Summary Functions, Maps
• Grouping, Sorting
• Data Types, Missing Values
• Renaming, Combining

100% Python 🐍.

20 machine learning questions that will make you think.

(Cool questions. Not the regular, introductory stuff that you find everywhere.)

🧵👇

1. Why is it important to introduce non-linearities in a neural network?

2. What are the differences between a multi-class classification problem and a multi-label classification problem?

3. Why does the use of Dropout work as a regularizer?

👇

4. Why you shouldn't use a softmax output activation function in a multi-label classification problem when using a one-hot-encoded target?

5. Does the use of Dropout in your model slow down or speed up the training process? Why?

👇

6. In a Linear or Logistic Regression problem, do all Gradient Descent algorithms lead to the same model, provided you let them run long enough?

7. Explain the difference between Batch Gradient Descent, Stochastic Gradient Descent, and Mini-batch Gradient Descent.

👇

8. What are the advantages of Convolution Neural Networks (CNN) over a fully connected network for image classification?

9. What are the advantages of Recurrent Neural Networks (RNN) over a fully connected network when working with text data?

👇

Some of my machine learning books.

Hands-On Machine Learning from @aureliengeron and Deep Learning with Python from @fchollet.

Do you know what's better than a machine learning model?

Two models.

More than one model working together to solve a problem is called "an emsemble." A simple way to build this is having each model vote for an answer.

But there's a problem with this approach: ↓

I'm gonna focus here on image classification.

Let's assume you built two different models:

• Model 1: A ResNet model.
• Model 2: A one-shot model (Siamese network.)

They both solve the same problem, so you want to combine their results to pick the right answer.

The problem is that you have two models, so voting is not trivial.

What happens in this case?

• Model 1's answer: Class A
• Model 2's answer: Class B

Which one do you select?

Notice that this problem is not limited to an even number of models.

You could have 3 models, each giving you a different answer.

How do you decide which answer to choose?

There are multiple ways to approach this problem. I'll mention a few different ideas on this thread.

Important: Some of these ideas might not be feasible depending on your context. They have worked for me before on different situations, but every problem is different.

RANI NAIKI DEVI AND THE BATTLE OF KASAHRADA

Mohammad Ghori, the young Ghurid Prince conquered Ghaznavids in Afghanistan in the year 1173 CE. He conducted some successful raids into the Indian territory, which even Mahmud Ghazni & the Persians couldn't do.

First&foremost,Ghori invaded states of Multan &Uch in India.After this he turned to southern states of Gujarat &Rajputana.Everybody knows this about Ghori,but what most pple r unaware of is the defeat he suffered at hands of Chalukyan Queen Naiki Devi in 1178 Battle of Kasahrada.

When he marched southwards, his first target was the prosperous fortified town of Anhilwara Patan.
It was the capital of Chalukyas(also known as Solankis of Gujarat) which was established by Vanraj of Chapotkata Dynasty in 8th century.

American historian Tertius Chandler states that it was the 10th largest city in the world at that time. The history of Chalukyas has been written by many historians, but the valour of the Great Queen Naiki Devi remains unsung.

Born to the Kadamba King Paramardin of Goa,Naiki Devi was well trained in sword fighting, horse riding, strategy & every other subject of Statesmanship. She was married to King Ajaypala of Gujarat who sat on throne in 1171CE. Unfortunately,the King died within 4 yrs of his rule.

This is my son, Sam. He’s 5. And today he learned how shitty and harmful #ToxicMasculinity is. My rage meter is spiking right now so excuse me if this is a little raw but there are some things I want to say about BS #gender norms (a thread)

Sam is my middle child & he’s a terror. A “boy’s boy” as so many (not me) would say. He’s rough and tumble, he’s loud, he’s always dirty, loves trucks, plays sports and knee drops me from the couch. But he also loves a lot of “girl” things.

Sam has a collection of purses because he likes to carry things around. And he also loves to have his nails painted bright colors because he thinks they “look beautiful.” And he’s right – they are beautiful…

So he proudly wore his red nail polish to kindergarten this morning because Sam has absolutely no concept of nail polish only being for girls or reason to think anyone would possibly have a problem with beautiful nails.

But his classmates did have a problem. A big one. Sam was ridiculed for being a boy with nail polish. They called him names and told him to take it off. This lasted the entire day.

Sri Gurubhyo Namah.
Some tweets on Adi Shankaracharya and in particular the Guru Parampara of @sringerimath. [I had done this series earlier 5 years ago on account of Shishya Sweekaram].

Adi Shankara established the Sringeri Peetham as the 1st of 4 amnaaya peetams.

The four being
1. Sarada Peetam at Sringeri.
2. Govardhana Peetam at Puri
3. Kalika at Dwaraka
4. Jyothir at Badarikashramam.

He installed his 4 most prominent shishyas as heads of the peetams.

Sureshwaracharya was assigned to Sringeri as its head.

Sringeri is a corruption of Rshyashrunga giri.

Rshyashrunga maharshi [and his father Sri Vibandhaka Maharshi] did their tapas at this place.

It is at Sringeri that Shankara spent 12 of His precious 32 years!!

That gives you and idea how much He loved this place.

Rshyashruga maharshi had a horn on his forehead, a result of being born to a deer. His mere presence was enough to shower rains!!

Rshyashrunga was one who led Putrakamesthi Yaagam of Dasaratha Maharaj and which resulted in Sri Rama's birth!!

@buzz_chronicles @AchuthArora @FitFounder @rattibha Cool!

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