udaclivyj zaberet 35 000


Главная страница
Конфиденциальность
Информация для авторов
Наша миссия
 

 

89d08f9bab9985f67a92ef5bc5bce121





Формат Размер Скачать

Информация о видео


Название :  
Продолжительность :  
Пользователь :  id 910305469717
Дата публикации :   ript nonce=
Просмотры :   9ABloU8c3tFZfQAekw
Понравилось :   1,306
Не понравилось :   22


Кадры из видео



yt:cc=on, data science, Data Science full course, data science for beginners, data science course, data science tutorial, data science training, introduction to data science, data science tutorial for beginners, data scientist, what is data science, Learn Data Science, who is a data scientist, data science skills, statistics for data science, edureka, python data science tutorial, data science edureka, python edureka, machine learning edureka, Edureka data science,



Описание к видео



Комментарии к видео



edureka!
Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Edureka Data Science Masters Certification Curriculum, Visit our Website: bit.ly/3sw3tJj (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎")
Комментарий от : edureka!


Atreya Raghuvanshi
its great but could you provide the pdf of this
Комментарий от : Atreya Raghuvanshi


parnika kansal
its a very great course. Could I please request you to provide me the slides used in the video?
Комментарий от : parnika kansal


Oishik Sinha
Thank You so much 👌🏻👍🏻
Edureka !!
This was amazing

Комментарий от : Oishik Sinha


Yashasvi Mahajan
Best video lectures available right now.
Can you plz tell how can i get the slides of the series??

Комментарий от : Yashasvi Mahajan


hamid awan
Amazing work, very professional. Can I please get these data sets used?
Комментарий от : hamid awan


Rajesh Natarajan
Awesome
Комментарий от : Rajesh Natarajan


Anuradha Tarpe
Do you provide certificate as well? by taking test on this?
Комментарий от : Anuradha Tarpe


TheAbdou27
Can we please get the dataset files you guys used so that we can follow along ?
Комментарий от : TheAbdou27


Sahlul Furqon
Yasss thankyou I find this video no ads
Комментарий от : Sahlul Furqon


BASHARRAT HARIS
Very informative and helpful video , could you please tell me where i can obtain the jupyter notebooks used in the videos form
Комментарий от : BASHARRAT HARIS


Anil Roy Dubey
Excellent excellent excellent excellent excellent!! Keep excelling
Комментарий от : Anil Roy Dubey


PERSONALITY GROWTH
Could you plz send this course slides at gmail: waqasirfanasad@gmail.com.
Комментарий от : PERSONALITY GROWTH


PERSONALITY GROWTH
Could you plz share your presentation of this cousre thnks 😊 email : waqasirfanasad@gmail.com
Комментарий от : PERSONALITY GROWTH


Ahmed Fahmy
Great work, shall you send me the presented material odd or ppt please my email is ahmedfahmyaee@yahoo.com
Комментарий от : Ahmed Fahmy


Data
00:00 Agenda
2:44 Introduction to Data Science
9:55 Data Analysis at Walmart
13:20 What is Data Science?
14:39 Who is a Data Scientist?
16:50 Data Science Skill Set
21:51 Data Science Job Roles
26:58 Data Life Cycle
30:25 Statistics & Probability
34:31 Categories of Data
34:50 Qualitative Data
36:09 Quantitative Data
39:11 What is Statistics?
41:32 Basic Terminologies in Statistics
42:50 Sampling Techniques
45:31 Random Sampling
46:20 Systematic Sampling
46:50 Stratified Sampling
47:54 Types of Statistics
50:38 Descriptive Statistics
55:52 Measures of Spread
55:56 Range
56:44 Inter Quartile Range
58:58 Variance
59:36 Standard Deviation
1:14:25 Confusion Matrix
1:19:16 Probability
1:24:14 What is Probability?
1:27:13 Types of Events
1:27:58 Probability Distribution
1:28:15 Probability Density Function
1:30:02 Normal Distribution
1:30:51 Standard Deviation & Curve
1:31:19 Central Limit Theorem
1:33:12 Types of Probablity
1:33:34 Marginal Probablity
1:34:06 Joint Probablity
1:34:58 Conditional Probablity
1:35:56 Use-Case
1:39:46 Bayes Theorem
1:45:44 Inferential Statistics
1:56:40 Hypothesis Testing
2:00:34 Basics of Machine Learning
2:01:41 Need for Machine Learning
2:07:03 What is Machine Learning?
2:09:21 Machine Learning Definitions
2:!1:48 Machine Learning Process
2:18:31 Supervised Learning Algorithm
2:19:54 What is Regression?
2:21:23 Linear vs Logistic Regression
2:33:51 Linear Regression
2:25:27 Where is Linear Regression used?
2:27:11 Understanding Linear Regression
2:37:00 What is R-Square?
2:46:35 Logistic Regression
2:51:22 Logistic Regression Curve
2:53:02 Logistic Regression Equation
2:56:21 Logistic Regression Use-Cases
2:58:23 Demo
3:00:57 Implement Logistic Regression
3:02:33 Import Libraries
3:05:28 Analyzing Data
3:11:52 Data Wrangling
3:23:54 Train & Test Data
3:20:44 Implement Logistic Regression
3:31:04 SUV Data Analysis
3:38:44 Decision Trees
3:39:50 What is Classification?
3:42:27 Types of Classification
3:42:27 Decision Tree
3:43:51 Random Forest
3:45:06 Naive Bayes
3:47:12 KNN
3:49:02 What is Decision Tree?
3:55:15 Decision Tree Terminologies
3:56:51 CART Algorithm
3:58:50 Entropy
4:00:15 What is Entropy?
4:23:52 Random Forest
4:27:29 Types of Classifier
4:31:17 Why Random Forest?
4:39:14 What is Random Forest?
4:51:26 How Random Forest Works?
4:51:36 Random Forest Algorithm
5:04:23 K Nearest Neighbour
5:05:33 What is KNN Algorithm?
5:08:50 KNN Algorithm Working
5:14:55 kNN Example
5:24:30 What is Naive Bayes?
5:25:13 Bayes Theorem
5:27:48 Bayes Theorem Proof
5:29:43 Naive Bayes Working
5:39:06 Types of Naive Bayes
5:53:37 Support Vector Machine
5:57:40 What is SVM?
5:59:46 How does SVM work?
6:03:00 Introduction to Non-Linear SVM
6:04:48 SVM Example
6:06:12 Unsupervised Learning Algorithms - KMeans
6:06:18 What is Unsupervised Learning?
6:06:45 Unsupervised Learning: Process Flow
6:07:17 What is Clustering?
6:09:15 Types of Clustering
6:10:15 K-Means Clustering
6:10:40 K-Means Algorithm Working
6:16:17 K-Means Algorithm
6:19:16 Fuzzy C-Means Clustering
6:21:22 Hierarchical Clustering
6:22:53 Association Clustering
6:24:57 Association Rule Mining
6:30:35 Apriori Algorithm
6:37:45 Apriori Demo
6:40:49 What is Reinforcement Learning?
6:42:48 Reinforcement Learning Process
6:51:10 Markov Decision Process
6:54:53 Understanding Q - Learning
7:13:12 Q-Learning Demo
7:25:34 The Bellman Equation
7:48:39 What is Deep Learning?
7:52:53 Why we need Artificial Neuron?
7:54:33 Perceptron Learning Algorithm
7:57:57 Activation Function
8:03:14 Single Layer Perceptron
8:04:04 What is Tensorflow?
8:07:25 Demo
8:21:03 What is a Computational Graph?
8:49:18 Limitations of Single Layer Perceptron
8:50:08 Multi-Layer Perceptron
8:51:24 What is Backpropagation?
8:52:26 Backpropagation Learning Algorithm
8:59:31 Multi-layer Perceptron Demo
9:01:23 Data Science Interview Questions

Комментарий от : Data


supriya singh
is this enough??
Комментарий от : supriya singh


Satyendra
Hi I am not related to any of the branches neither have degree or certification of any kind still I find it interesting and want to learn it as these are the skills of future
Can anyone please suggest if I have persued BA Maths then what should I do

Комментарий от : Satyendra


Deep's Learning Studio
Thank you so much.....
Комментарий от : Deep's Learning Studio


Shaik saqafee Talaha
Is this course is sufficient for begginers
Комментарий от : Shaik saqafee Talaha


rameez khan
am civil engineer|| can i learned?? for data science engineer.??
Комментарий от : rameez khan


Anish Apostate
could you please clear me the dataset at 1:11:00 of video, from where did you get 6 instances true & 8 instances false in the humidity dataset. I am getting 9 yes and 5 no. Please help me out.
Комментарий от : Anish Apostate


Croma Campus
Thanks for sharing this information Edureka. Really Helpful
Комментарий от : Croma Campus


Brainstorming & sharing
👍👍👍👍👍👍👍
Комментарий от : Brainstorming & sharing


Zawar Allahbuxbhatti
Hello edureka team, I really loved your efforts to make such helpful content, now I want to know is that all a data scientist needs to know or this was just for beginners?
Thanks alot anyway 😊

Комментарий от : Zawar Allahbuxbhatti


suchit patil
Can I apply for job after completing this course ?
Комментарий от : suchit patil


Jai Singh
You are best I'm not
Комментарий от : Jai Singh


Rakesh Yadav
you are providing course in hindi or english
Комментарий от : Rakesh Yadav


Rishav Pandit
I want the data sets which you have used in this video, can you send me, please?
Комментарий от : Rishav Pandit


Alam Ansari
Please send me the datasets my email naiyarans@gmail.com
Комментарий от : Alam Ansari


Kassahu alebel
thank you how I get document
Комментарий от : Kassahu alebel


Aruna Duvvuri
Thank you very much for the course edureka. please can I get the slides used through my mail?
my email id is aravind294a@gmail.com.
thanks

Комментарий от : Aruna Duvvuri


Malleswari malli
Nice explanation , very easy to understand to the beginners also #thank you for providing absolutely free in youtube..#very helpful for the researchers
Комментарий от : Malleswari malli


Alina Mirza
Ans probability 11/17
Комментарий от : Alina Mirza


Alan Ajanovic
Hi Edureka, can you pls share the dataset used in your course? Where can I send you my id? Thanks a lot!
Комментарий от : Alan Ajanovic


VINDARA
Learning Data science with python is good or without python??
Комментарий от : VINDARA


TechCurious
00:00 Agenda
2:44 Introduction to Data Science
9:55 Data Analysis at Walmart
13:20 What is Data Science?
14:39 Who is a Data Scientist?
16:50 Data Science Skill Set
21:51 Data Science Job Roles
26:58 Data Life Cycle
30:25 Statistics & Probability
34:31 Categories of Data
34:50 Qualitative Data
36:09 Quantitative Data
39:11 What is Statistics?
41:32 Basic Terminologies in Statistics
42:50 Sampling Techniques
45:31 Random Sampling
46:20 Systematic Sampling
46:50 Stratified Sampling
47:54 Types of Statistics
50:38 Descriptive Statistics
55:52 Measures of Spread
55:56 Range
56:44 Inter Quartile Range
58:58 Variance
59:36 Standard Deviation
1:14:25 Confusion Matrix
1:19:16 Probability
1:24:14 What is Probability?
1:27:13 Types of Events
1:27:58 Probability Distribution
1:28:15 Probability Density Function
1:30:02 Normal Distribution
1:30:51 Standard Deviation & Curve
1:31:19 Central Limit Theorem
1:33:12 Types of Probablity
1:33:34 Marginal Probablity
1:34:06 Joint Probablity
1:34:58 Conditional Probablity
1:35:56 Use-Case
1:39:46 Bayes Theorem
1:45:44 Inferential Statistics
1:56:40 Hypothesis Testing
2:00:34 Basics of Machine Learning
2:01:41 Need for Machine Learning
2:07:03 What is Machine Learning?
2:09:21 Machine Learning Definitions
2:!1:48 Machine Learning Process
2:18:31 Supervised Learning Algorithm
2:19:54 What is Regression?
2:21:23 Linear vs Logistic Regression
2:33:51 Linear Regression
2:25:27 Where is Linear Regression used?
2:27:11 Understanding Linear Regression
2:37:00 What is R-Square?
2:46:35 Logistic Regression
2:51:22 Logistic Regression Curve
2:53:02 Logistic Regression Equation
2:56:21 Logistic Regression Use-Cases
2:58:23 Demo
3:00:57 Implement Logistic Regression
3:02:33 Import Libraries
3:05:28 Analyzing Data
3:11:52 Data Wrangling
3:23:54 Train & Test Data
3:20:44 Implement Logistic Regression
3:31:04 SUV Data Analysis
3:38:44 Decision Trees
3:39:50 What is Classification?
3:42:27 Types of Classification
3:42:27 Decision Tree
3:43:51 Random Forest
3:45:06 Naive Bayes
3:47:12 KNN
3:49:02 What is Decision Tree?
3:55:15 Decision Tree Terminologies
3:56:51 CART Algorithm
3:58:50 Entropy
4:00:15 What is Entropy?
4:23:52 Random Forest
4:27:29 Types of Classifier
4:31:17 Why Random Forest?
4:39:14 What is Random Forest?
4:51:26 How Random Forest Works?
4:51:36 Random Forest Algorithm
5:04:23 K Nearest Neighbour
5:05:33 What is KNN Algorithm?
5:08:50 KNN Algorithm Working
5:14:55 kNN Example
5:24:30 What is Naive Bayes?
5:25:13 Bayes Theorem
5:27:48 Bayes Theorem Proof
5:29:43 Naive Bayes Working
5:39:06 Types of Naive Bayes
5:53:37 Support Vector Machine
5:57:40 What is SVM?
5:59:46 How does SVM work?
6:03:00 Introduction to Non-Linear SVM
6:04:48 SVM Example
6:06:12 Unsupervised Learning Algorithms - KMeans
6:06:18 What is Unsupervised Learning?
6:06:45 Unsupervised Learning: Process Flow
6:07:17 What is Clustering?
6:09:15 Types of Clustering
6:10:15 K-Means Clustering
6:10:40 K-Means Algorithm Working
6:16:17 K-Means Algorithm
6:19:16 Fuzzy C-Means Clustering
6:21:22 Hierarchical Clustering
6:22:53 Association Clustering
6:24:57 Association Rule Mining
6:30:35 Apriori Algorithm
6:37:45 Apriori Demo
6:40:49 What is Reinforcement Learning?
6:42:48 Reinforcement Learning Process
6:51:10 Markov Decision Process
6:54:53 Understanding Q - Learning
7:13:12 Q-Learning Demo
7:25:34 The Bellman Equation
7:48:39 What is Deep Learning?
7:52:53 Why we need Artificial Neuron?
7:54:33 Perceptron Learning Algorithm
7:57:57 Activation Function
8:03:14 Single Layer Perceptron
8:04:04 What is Tensorflow?
8:07:25 Demo
8:21:03 What is a Computational Graph?
8:49:18 Limitations of Single Layer Perceptron
8:50:08 Multi-Layer Perceptron
8:51:24 What is Backpropagation?
8:52:26 Backpropagation Learning Algorithm
8:59:31 Multi-layer Perceptron Demo
9:01:23 Data Science Interview Questions

Комментарий от : TechCurious


Samindi Godakanda
Great work...thank you very much
Комментарий от : Samindi Godakanda


Thota Chandrika
It's really useful course ..thanks for providing it's for free
Комментарий от : Thota Chandrika


syed saba
Humanity needed Edureka! ❤
Комментарий от : syed saba


Sujaul Suvon
I think this course should be helpful for my academic education & carrier build up.
ThAnK YoU😍
Note:I am a student at Department of Statistics BsC(Hons)

Комментарий от : Sujaul Suvon


SARTHAK JAISWAL
I love her teaching style...I'm gonna finish this in 2 days, it's so good and easy to learn...wasted 6 months in college learning this and they taught in much detail in 10 hours... it's amazing.
Комментарий от : SARTHAK JAISWAL


Ankit Nayal
can i get all the dataset
Комментарий от : Ankit Nayal


Pothuluru Veerareddy
Thanks edureka
Комментарий от : Pothuluru Veerareddy


HRP Productions
Bro if I learn this 10 hrs course, will I get a job in data science fielf
Комментарий от : HRP Productions


Sharath Premnath
If I complete this 10 hour course and then want to get the certificate, is it possible?
Комментарий от : Sharath Premnath


Gouse chinnu
can science student learn data science i dont have minimum computer
knowledge also

Комментарий от : Gouse chinnu


Nazrin Karimova
Hi can you send me solution of examole which in the bayes theorem?
Комментарий от : Nazrin Karimova


thasneema umer
Thank you very much for this great videos.
Комментарий от : thasneema umer


Akanksha_50
Sir,please share the decision tree algorithm..
Комментарий от : Akanksha_50


Aditi Gupta
is it mandatory to have math in 12th or college level to be a data scientist?
Комментарий от : Aditi Gupta


Mohit Kotta
Thanks a lot Edurika , I am in 9th for now and I am looking at data science as a career option . I have finished 10 minutes of the video and the topic really interested me , I will be finishing the video in 2 weeks and hopefully I get a fair idea of how Data science works . Again , thanks a lot 😄
Комментарий от : Mohit Kotta


Pandu Devarasetti
tq edureka it is very useful to all
Комментарий от : Pandu Devarasetti


ARUN RAJ
SUPER EDUREKA
Комментарий от : ARUN RAJ


Emmanuel Tettey Lawer
Wow, this is great
Can I please get the datasets used in this course

Комментарий от : Emmanuel Tettey Lawer


mr srk entertainment
Helpful or useful Amazing video thanku you so much edureka! team
Комментарий от : mr srk entertainment


Puneet Tiwari
Simply woww...
Комментарий от : Puneet Tiwari


Mersiha Ćeranić
Hello. Awesome video! Could you please share datasets with me?
Thank you.

Комментарий от : Mersiha Ćeranić


Chitra Kalpesh Vasvani
U ppl are doing amazing job...keep it up...
Комментарий от : Chitra Kalpesh Vasvani


Prabu Venkatesan
Awosome job edureka team
Комментарий от : Prabu Venkatesan


Anubha Gupta
THankyouu for this course
Комментарий от : Anubha Gupta


Brandon cheng
18:20
Комментарий от : Brandon cheng


saryuable
Datasets ?
Комментарий от : saryuable


Dishant Kumbhar
Love u edureka!
Really u just not made us understood concept but coding also.
❣️🙏

Комментарий от : Dishant Kumbhar


Ghulam Mujtaba Adil
may God bless you people .
Комментарий от : Ghulam Mujtaba Adil


Dishant Kumbhar
Guys this is really an awesome tutorial, you won't find out on another channel.
Like if u r watching this video

Thank you Edureka for making us understand complex thing in simplest manner.

Комментарий от : Dishant Kumbhar


VISHWANATH T S
00:00 Agenda
2:44 Introduction to Data Science
9:55 Data Analysis at Walmart
13:20 What is Data Science?
14:39 Who is a Data Scientist?
16:50 Data Science Skill Set
21:51 Data Science Job Roles
26:58 Data Life Cycle
30:25 Statistics & Probability
34:31 Categories of Data
34:50 Qualitative Data
36:09 Quantitative Data
39:11 What is Statistics?
41:32 Basic Terminologies in Statistics
42:50 Sampling Techniques
45:31 Random Sampling
46:20 Systematic Sampling
46:50 Stratified Sampling
47:54 Types of Statistics
50:38 Descriptive Statistics
55:52 Measures of Spread
55:56 Range
56:44 Inter Quartile Range
58:58 Variance
59:36 Standard Deviation
1:14:25 Confusion Matrix
1:19:16 Probability
1:24:14 What is Probability?
1:27:13 Types of Events
1:27:58 Probability Distribution
1:28:15 Probability Density Function
1:30:02 Normal Distribution
1:30:51 Standard Deviation & Curve
1:31:19 Central Limit Theorem
1:33:12 Types of Probability
1:33:34 Marginal Probability
1:34:06 Joint Probability
1:34:58 Conditional Probability
1:35:56 Use-Case
1:39:46 Bayes Theorem
1:45:44 Inferential Statistics
1:56:40 Hypothesis Testing
2:00:34 Basics of Machine Learning
2:01:41 Need for Machine Learning
2:07:03 What is Machine Learning?
2:09:21 Machine Learning Definitions
2:11:48 Machine Learning Process
2:18:31 Supervised Learning Algorithm
2:19:54 What is Regression?
2:21:23 Linear vs Logistic Regression
2:33:51 Linear Regression
2:25:27 Where is Linear Regression used?
2:27:11 Understanding Linear Regression
2:37:00 What is R-Square?
2:46:35 Logistic Regression
2:51:22 Logistic Regression Curve
2:53:02 Logistic Regression Equation
2:56:21 Logistic Regression Use-Cases
2:58:23 Demo
3:00:57 Implement Logistic Regression
3:02:33 Import Libraries
3:05:28 Analyzing Data
3:11:52 Data Wrangling
3:23:54 Train & Test Data
3:20:44 Implement Logistic Regression
3:31:04 SUV Data Analysis
3:38:44 Decision Trees
3:39:50 What is Classification?
3:42:27 Types of Classification
3:42:27 Decision Tree
3:43:51 Random Forest
3:45:06 Naive Bayes
3:47:12 KNN
3:49:02 What is a Decision Tree?
3:55:15 Decision Tree Terminologies
3:56:51 CART Algorithm
3:58:50 Entropy
4:00:15 What is Entropy?
4:23:52 Random Forest
4:27:29 Types of Classifier
4:31:17 Why Random Forest?
4:39:14 What is Random Forest?
4:51:26 How Random Forest Works?
4:51:36 Random Forest Algorithm
5:04:23 K Nearest Neighbour
5:05:33 What is KNN Algorithm?
5:08:50 KNN Algorithm Working
5:14:55 kNN Example
5:24:30 What is Naive Bayes?
5:25:13 Bayes Theorem
5:27:48 Bayes Theorem Proof
5:29:43 Naive Bayes Working
5:39:06 Types of Naive Bayes
5:53:37 Support Vector Machine
5:57:40 What is SVM?
5:59:46 How does SVM work?
6:03:00 Introduction to Non-Linear SVM
6:04:48 SVM Example
6:06:12 Unsupervised Learning Algorithms - KMeans
6:06:18 What is Unsupervised Learning?
6:06:45 Unsupervised Learning: Process Flow
6:07:17 What is Clustering?
6:09:15 Types of Clustering
6:10:15 K-Means Clustering
6:10:40 K-Means Algorithm Working
6:16:17 K-Means Algorithm
6:19:16 Fuzzy C-Means Clustering
6:21:22 Hierarchical Clustering
6:22:53 Association Clustering
6:24:57 Association Rule Mining
6:30:35 Apriori Algorithm
6:37:45 Apriori Demo
6:40:49 What is Reinforcement Learning?
6:42:48 Reinforcement Learning Process
6:51:10 Markov Decision Process
6:54:53 Understanding Q - Learning
7:13:12 Q-Learning Demo
7:25:34 The Bellman Equation
7:48:39 What is Deep Learning?
7:52:53 Why we need Artificial Neuron?
7:54:33 Perceptron Learning Algorithm
7:57:57 Activation Function
8:03:14 Single Layer Perceptron
8:04:04 What is Tensorflow?
8:07:25 Demo
8:21:03 What is a Computational Graph?
8:49:18 Limitations of Single Layer Perceptron
8:50:08 Multi-Layer Perceptron
8:51:24 What is Backpropagation?
8:52:26 Backpropagation Learning Algorithm
8:59:31 Multi-layer Perceptron Demo
9:01:23 Data Science Interview Questions

Комментарий от : VISHWANATH T S


Aryan menon 16
Edureka is great 👍👏😊
Much love to you guys..

Комментарий от : Aryan menon 16


Kumaran bala
love edureka,
Комментарий от : Kumaran bala


mbagraduate application
Nice course! Greetings from UK
Комментарий от : mbagraduate application


Harsh Ranjan
Thank you, it helps me lot
Комментарий от : Harsh Ranjan


shubh verma
thank you so much
Комментарий от : shubh verma


Khayima Arnisti
Thank you very much for your video tutorials, its very help full to me
Комментарий от : Khayima Arnisti


andrzej21111
Thank You so much
Комментарий от : andrzej21111


Karthika Ravindran
I am 11 years old .......
I am studying it from age 6

Комментарий от : Karthika Ravindran


Shreenidhi R
Excellent video!! Is it possible upload the datasets used in this folder?? Maybe like a drive folder
Комментарий от : Shreenidhi R


Drishal Ballaney
where are the datasets?
Комментарий от : Drishal Ballaney


maheswari mahi
Can I get the datasets used in this course??
Комментарий от : maheswari mahi


Rishabh Kumar
This is what we wanted.. Thank u Edureka for providing us with such a good video for free😊😊
Комментарий от : Rishabh Kumar


Vignesh Pai
Where I can get code and datasets?
Комментарий от : Vignesh Pai


Anything for Fun
Thank you such much for providing precious stuff.
Комментарий от : Anything for Fun


om shah #prayagraj
It's very helpful video ...
Комментарий от : om shah #prayagraj


akhil shaganti
Amazing content, loved it!
Комментарий от : akhil shaganti


Garry
what is the difference between ur course on youtube and paid ones on your website?
Комментарий от : Garry


Debojyoti Mandal
Just Completed the 10hrs theory.
Комментарий от : Debojyoti Mandal


Dee
It's a great beginners course. Loved it, thank you for getting me started off.
Комментарий от : Dee


Naaz
Thank you for this wonderful course 💗
Комментарий от : Naaz


All About Studies
1:00:00
Комментарий от : All About Studies


Rupesh Sunuwar
Thanks for the information and knowledge❤
Комментарий от : Rupesh Sunuwar


Mail Rama
Im just 12 years old and excited about data science
Комментарий от : Mail Rama


Ravi Ranjan
Great thanks for sharing this lecture.
Комментарий от : Ravi Ranjan


Malik Muhammad Ali
Thabkyou so much Edureka ❤
Комментарий от : Malik Muhammad Ali


Panchanan Sahoo
Thanks edureka for this video 💗💗
Комментарий от : Panchanan Sahoo


Gohar Ali
Please we need this course in hindi
Комментарий от : Gohar Ali


Daniel Mwaura
Awesome video. Is it possible to have the data used?
Комментарий от : Daniel Mwaura


yash shukla
Biggest fan and i just watch edureka videos only
Комментарий от : yash shukla


Giri Vardhana Kumar
Edureka team gets 5 star room in heaven

Thanks for the amazing video I love this video a lot

Комментарий от : Giri Vardhana Kumar


Utkarsha Nishad
Thank you so much edureka! for this video. This is so beneficial for me as a beginner. 😊😊
Комментарий от : Utkarsha Nishad


Saksham Sharma
thankyou edureka for being in youtube and giving us the best courses free without any cost
love you edureka
thanks keep it up

Комментарий от : Saksham Sharma


Hashem Alattas
thanks
Комментарий от : Hashem Alattas



Похожие на видео