The document outlines assignments for students in a data science course. It lists the roll numbers of 31 students and assigns each student two mini-projects related to data analysis, data classification, and predictive modeling. The mini-projects involve case studies, analyzing COVID vaccination data, developing a movie recommendation model, and classifying tweets using datasets from Kaggle.

1. TE - A DSBDA MiniProject Assignment
Roll No. Name of the student MiniProject1 MiniProject 2
3101001 ADHAV SOHAM GANESH
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101002 AMBORKAR BHAVESH SUNIL
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101003 ANUBHAW MISHRA
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101004 BADE AASTHA RAMESH
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101005 BENDALE AYUSH YOGESH
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101006 Bhide Ashwini Vinay
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101007 BORA MITALI MAHENDRA
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101008 CHAUDHARI ANIKET RAJENDRA
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated

2. 3101009 CHAUDHARI DNYANESHWAR JAYANT
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101010 CHAUDHARI MANISHA KANARAM
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101011 CHAVAN VEDANG GANESH
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101012 Dadge Krishna Anil
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets

3. 3101013 DALAL PREYASH PARESH
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101014 DESAI NIRANJAN VIKAS
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101015 DESHMUKH OM RAMDAS
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101016 DHAMAL OMKAR DATTATRAY
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101017 DHANAWADE SAKSHI HANUMANT
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101018 DHANE ANIKET ARUN
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101019 Dhole Yash Bandu
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.

4. 3101020 DUSHING SHIVANI PRASHANT
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101021 Gaikwad Rutuja RAVINDRA
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101022 GAIKWAD VIVEK SATISH
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101023 GANJALE SAURABH SANJAY
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101024 GHATTE PRATIK GAJANAN
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101025 HADOLE SAKSHI SHIVAJI
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101026 HEDAU VEDANT RAJESH
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101027 HOLE SAKSHI VIJAY
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101028 INGLE YASH RAJABHAU
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated

5. 3101029 JAGTAP GOURIE BABBAJEEH
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101030 Kale Vaibhav Bhausaheb
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101031 KARPE SAMRUDDHI AJIT
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101032 KHAIRE SWAMINI VINOD
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets

6. 3101033 KHARADE ROHIT SHAHAJI
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101034 Kharat Vishwajeet Dipak
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101035 KHIRID SAHIL GANESH
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101036 KHOLGADE CHETAN GAJANAN
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101037 KOTHAWADE CHIRAG RAJENDRA
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101038 LAVHALE ABHIJIT KADAJI
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101039 MADANE TUSHAR BHAGWAN
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.

7. 3101040 MAHAJAN PRASHANT RAMKRUSHNA
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101041 MALLICK NASIMA YASMIN ILIUS ALI
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101042 MEHKARKAR PRATHMESH GIRIPRASAD
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101043 MOHITE PRAJWAL RAGHAVENDRA
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101044 More Mrunali Sunil
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101045 MORE VISHAL SANJAY
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101046 NAGE AKANKSHA KANIPHNATH
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101047 NAWALKAR ANIKET GAJANAN
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101048 NIKAM RUTUJA RAMDAS
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated

8. 3101049 Padavi Harishchandra Ravindra
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101050 PANSARE NISARG MANOHAR
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101051 PARDESHI ADITI RAJENDRA
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101052 PARJANE KALYANI RAVINDRA
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets

9. 3101053 PATHAK NEHA MANOJ
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101054 PATIL PRANOTI PANDURANG
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101055 PAWAR PRAJWAL JAGDISH
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101056 PHADTARE VEDANT DILIP
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101057 PINGALE PANKAJ CHANGDEV
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101058 PRASAD SUNIL CHAWARE
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101059 PREET POCHAT
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.

10. 3101060 PUTALE KUNAL SHEKHAR
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101061 RELUSINGHANI PREET KAUR KULDEEPSINGH
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101062 RUTUJA MOHAN SATHE
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101063 SANDBHOR SHREYAS AMOL
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101064 SATPUTE DIPTI DEVRAM
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101065 SAWANT ROHIT RAJKUMAR
Write a case study on Global Innovation Network and Analysis (GINA). Components of
analytic plan are 1. Discovery business problem framed, 2. Data, 3. Model planning
analytic technique 4. Results and Key findings.
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101066 SHEKATKAR HIMANSHU SANJAY
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101067 SHELAKE TEJAS MILIND
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101068 Shinde Kunal Bharat
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated

11. 3101069 SHINDE MITESH RAMESH
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101070 SHINDE RAJWARDHAN SANJAY
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Use the following covid_vaccine_statewise.csv dataset and perform
following analytics on the
given dataset
https://www.kaggle.com/sudalairajkumar/covid19-in-india?
select=covid_vaccine_statewise.csv
a. Describe the dataset
b. Number of persons state wise vaccinated for first dose in India
c. Number of persons state wise vaccinated for second dose in India
d. Number of Males vaccinated
d. Number of females vaccinated
3101071 SAKSHI SIRGAN
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101072 SONPATKI SOHAN SUNIL
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets

12. 3101073 TEJWANI ANISH SHANKARLAL
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101074 TELI SHUBHANGI RAJENDRA
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101075 THANGE SAKSHI SANTOSHKUMAR
"Write a case study to process data driven for Digital Marketing OR Health care systems with
Hadoop Ecosystem components as shown. (Mandatory)
● HDFS: Hadoop Distributed File System
● YARN: Yet Another Resource Negotiator
● MapReduce: Programming based Data Processing
● Spark: In-Memory data processing
● PIG, HIVE: Query based processing of data services
● HBase: NoSQL Database (Provides real-time reads and writes)
● Mahout, Spark MLLib: (Provides analytical tools) Machine Learning algorithm
libraries
● Solar, Lucene: Searching and Indexing"
2. Use the following dataset and classify tweets into positive and
negative tweets.https://www.kaggle.com/ruchi798/data-science-tweets
https://www.kaggle.com/ruchi798/data-science-tweets
3101076 THORAT ABHIJIT KISAN
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101077 UBALE TEJAS SHAILESH
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.
3101078 WALUNJ OMKAR RAMDAS
Develop a movie recommendation model using the scikit-learn library in python.Refer
dataset https://github.com/rashida048/Some-NLP-Projects/blob/master/movie_dataset.
csv
Write a case study on Global Innovation Network and Analysis (GINA).
Components of analytic plan are 1. Discovery business problem
framed, 2. Data, 3. Model planning analytic technique 4. Results and
Key findings.