Deepanshu Choudhary
Deepanshu Choudhary
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Відео

How to do Principal Component Analysis in Machine Learning in python *SVM Classification Included*
Переглядів 1,6 тис.4 роки тому
Code : drive.google.com/file/d/1TCyM7_B56W4HVbFlLniFrZEMpcx4bX8n/view?usp=sharing In this video i implement the Principal Component Analysis in Python over the Scikit Learn Breast Cancer Dataset. Further down the line I did the Support Vector Machines Classification and reach up to 95% accuracy. Support the channel, Hit Like and Subscribe #Machinelearning #supportvectormachine #pca #datascience
How to implement the LSTM Network on a Time-series, (Explained In Easier way), Code included
Переглядів 2014 роки тому
Code : drive.google.com/file/d/19gvayUwbriD2ScdSKP9alTSFiQyYN5g_/view?usp=sharing In this video i implemented a LSTM Network in a Simple and Easy to understand, way. Sometimes LSTMs, RNNs may haunt beginners because of so extra moving parts, but with sufficient practice and good direction one can easily master over it, Here i made an effort to do the same, LSTM Neural Networks can be so powerfu...
How to convert Time Series data to Supervised Data *IN HINDI* CLEAR EXPLANATION
Переглядів 8534 роки тому
#machinelearning #deeplearning In this video i demonstrated that how to convert time series data to supervised data format , to use it into supervised Machine Learning or Deep Learning Models like LSTM , CNN, MLP etc.
QUEUE Implementation | using Linked List | Python in 10 minutes
Переглядів 5 тис.5 років тому
Queue is an abstract data structure, somewhat similar to Stacks. Unlike stacks, a queue is open at both its ends. One end is always used to insert data (enqueue) and the other is used to remove data (dequeue). Queue follows First-In-First-Out methodology, i.e., the data item stored first will be accessed first. Link to Python Notebook: github.com/proffdeep/Queue_using_linked_list/blob/master/Qu...
Binary Search Algorithm using recursion python implementation.
Переглядів 9635 років тому
In computer science, binary search, also known as half-interval search,[1] logarithmic search,[2] or binary chop,[3] is a search algorithm that finds the position of a target value within a sorted array.[4][5] Binary search compares the target value to the middle element of the array. If they are not equal, the half in which the target cannot lie is eliminated and the search continues on the re...
Stack Implimentation | PYTHON | Data structures |
Переглядів 1315 років тому
Stack works on the principle of “Last-in, first-out”. Also, the inbuilt functions in Python make the code short and simple. To add an item to the top of the list, i.e., to push an item, we use append() function and to pop out an element we use pop() function. These functions work quiet efficiently and fast in end operations.

КОМЕНТАРІ

  • @shinazz160
    @shinazz160 Рік тому

    Your contents are so much useful for me.Thanks a lot

  • @me.6803
    @me.6803 2 роки тому

    Thanku helpful

  • @madushani6844
    @madushani6844 2 роки тому

    😪 sleepy, anyway thnks

  • @StudyBuddy_in
    @StudyBuddy_in 2 роки тому

    Teach at our channel !!

  • @prashantkumargupta4312
    @prashantkumargupta4312 2 роки тому

    helpful video

  • @GSMusix
    @GSMusix 3 роки тому

    Bro Y ur voice is too low.. 😒

  • @vishalRaj-nv4bs
    @vishalRaj-nv4bs 3 роки тому

    Thank you, Sir. if possible plz also post the link for code.

  • @anirudhatalmale5575
    @anirudhatalmale5575 3 роки тому

    superb explanation

  • @amrataagrawal5875
    @amrataagrawal5875 3 роки тому

    thanks for explaining it nicely

  • @cheerbust4888
    @cheerbust4888 3 роки тому

    How did you choose pca n_components=2?

  • @gjorgjimarushovski7125
    @gjorgjimarushovski7125 3 роки тому

    Hello Deepanshu thank you for video. I have a couple of questions or some help with my project. I try to make predictions for 30 days. First i split train data 70 % and test data 30 % . I reshape them i make create model and finish train. That's everything good. I want to make prediction from test data for future 30 days. I take last 100 days from test data to make prediction for future 30 days. It have new output for every 100 days. My question is from where come that output

  • @014_nasreenparween5
    @014_nasreenparween5 4 роки тому

    Image data pe bhi bno lo bhi,jisko dekho breast cancer pe kr rha hai or CSV file le rha hai👎👎👎

  • @shoaibshoobi7131
    @shoaibshoobi7131 4 роки тому

    can you guide us how to use PCA in Text data or how to prepare the text data for PCA based on features

  • @shoaibshoobi7131
    @shoaibshoobi7131 4 роки тому

    keep it up dude

  • @Mashter1028
    @Mashter1028 4 роки тому

    superb

  • @arihanttnandi
    @arihanttnandi 4 роки тому

    Thanks

  • @nishantbhushan3431
    @nishantbhushan3431 4 роки тому

    hello Nice video i just have one doubt self.last.next = new_node; self.last = new_node; # why newNode should be the last itself we have already pointed the new node with last.next then why need of self.last = new_node Thanks

    • @prashantkumargupta4312
      @prashantkumargupta4312 2 роки тому

      self.last.next = new_node; that means we add new node then (self.last.next = new_node) this is the location where we have to add

  • @ironfuse51
    @ironfuse51 4 роки тому

    Amazing 😍

  • @javeriabatool3555
    @javeriabatool3555 4 роки тому

    Good.

  • @javeriabatool3555
    @javeriabatool3555 4 роки тому

    I m looking for more videos on time series forecasting using deep learning from your end.

    • @deepanshuchoudhary4598
      @deepanshuchoudhary4598 4 роки тому

      Thanks for watching Javeria, Yeah sure, I'll be uploading more and more videos on time series, just stay tuned and support this channel.

  • @abhinavreddy5350
    @abhinavreddy5350 4 роки тому

    tq ............................... do more videos........

  • @deepanshuchoudhary4598
    @deepanshuchoudhary4598 5 років тому

    Any suggestion of improvement is highly appreciated, feel free to comment ! :)

  • @deepanshuchoudhary4598
    @deepanshuchoudhary4598 5 років тому

    This is a newbie channel, i highly assure that you're going to get valuable and quality content in future, apology for quality of this video, i'm still learning this stuff. Thanks :)