FAKE NEWS CLASSIFIER WITH MACHINE LEARNING ALGORITHMS USING Natural Language Processing- PART 1

Fake news is a type of propaganda where disinformation is intentionally spread through news outlets and/or social media outlets.

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[krishnaik]

Hello All, This video were for the members, but many of you all had requested this video. So I have uplaoded for everyone. It is also added in NLP playlist Happy Learning!!

[parthraghuwanshi]

People like u are gems who after working hard all days in office takes out time just to do post quality content that too being selfless I can truly understand how much good values a person has

[tejashshah]

At 10:48, CountVectorizer() should not be performed before train_test_split(). If you do, this leads to data leakage and is not correct. Correct way is to fit_transform() on train and transform() on test data.

[johnyjose]

Hi Krish, @ 8:28, why did you take messages['title'] ?? I think we should take messages['text']

[suresherriboyina]

Please upload Part 2, Because now we have so much of time, so keep upload new project videos

[thechaoticneuron]

Hello Krish, this is a great video. I started my learning into NLP with this. A small question;


I followed the entire procedure similarly and I implemented Logistic Regression at the end. It gave me a higher accuracy of 94% with less false positives and negatives as well.


I'm just keen to know how PassiveAggressive Classifier is said to be better for NLP applications and why not s simple logistic regression cannot be used.


Thank you :)

[themightylion]

Sir @ 8:28, why did you take messages['title'] ?? I think we should take messages['text'].

[vasanthrohith]

It's super useful🤩.... thanks for teaching ❤

[alexanderbalasky]

Great walkthrough but look into your audio!

[rajarshidgp]

time[15:40] - u r not able to see the because you had done reset_index - so the original index numbers have been lost

I am a machine learning engineer, I like that you post such videos but the problem with real data set is that there is no training data .

You have to collect and create your own training data . People who are watching this video don't know what is about to hit them once they enter this field.

It's not plug and play.

I spend 80% of my time creating data and processing it and only 20% actually doing ML

In one anomaly detection project we had to use db scan to find noise in the data then we marked the noise dp's as anomalous and cluster dp's as non anomalous. Then used that data to train our ANN.

[abhishekpurohit]

Just got 97% accuracy by combining both title and text....using passive aggresive classifier..

[pec]

Hi @Krish, shouldn't you create the bag of words on the X_train instead of the full dataset ? Otherwise the accuracy will not be the same when providing a new sentence

[samirpaul]

Hello Krish - This is an amazing video. I have been watching your videos and learned many things. Wonderful contribution towards the aspiring Machine Learning engineers. I have one question, request you to clarify. After this Bag-of-words/TF-IDF model is built, for new sentences, how do we construct the input featues (to be passed to predict function of the model). If such explanation exists in any other video, please point me to that, else would request you to make a short video on this, this will be immensely helpful. Thank you again. - Samir Paul

[tanishbothra]

Hello, Suppose we need to add more features in our X which are not text..i.e suppose we get a sparse matrix after count vectorizer and now we have one more feature length and we want both features.How to combine both?

[mdenamulhaque]

Dear Krish, for being a data scientist should we need to learn SQL or something like this? If it's need then why it's absent in your data science play list or do you have any idea in future for that. I'm very confused.please info.thnx

[surajthallapalli]

Hi Sir, I guess there is a data leakage problem. First we need to split train and test and later we have to apply Countvectorizer rite? In the video first the CountVectorizer is applied and later train and test split is done. Please clarify this.

[abhishekpurohit]

Sir you've not uploaded the video on passive aggressive classifier....Please upload it Sir!!

[pmcoffee]

@Krish Naik Sir do you provide paid personal consultation on hourly basis? Its there any way i can connect with you?

[mohammedzia]

Hi Krish, ,
It was a nice video, but I have one ques, the condition "If score = previous_score" will satisfy every time right ? As you have set the value of previous_score to ZERO. So what is the use of this ? Don't we have to assign score value to previous_score like this "previous_score = score", after the IF condition ?