Date: 17-10-2023
Company name - PWC
Role : ML Engineer
Topic: dbscan, joins in SQL, gridsearch vs random search, deployment

1. What is DBSCAN Clustering?

DBSCAN groups ‘densely grouped’ data points into a single cluster. It can identify clusters in large spatial datasets by looking at the local density of the data points. The most exciting feature of DBSCAN clustering is that it is robust to outliers. It also does not require the number of clusters to be told beforehand, unlike K-Means, where we have to specify the number of centroids.

2. What are the different forms of joins in a table?

SQL has many kinds of different joins including INNER JOIN, SELF JOIN, CROSS JOIN, and OUTER JOIN. In fact, each join type defines the way two tables are related in a query. OUTER JOINS can further be divided into LEFT OUTER JOINS, RIGHT OUTER JOINS, and FULL OUTER JOINS.

3.How is the grid search parameter different from the random search?

Model Hyperparameter tuning is very useful to enhance the performance of a machine learning model. The only difference between both the approaches is in grid search we define the combinations and do training of the model whereas in RandomizedSearchCV the model selects the combinations randomly. Both are very effective ways of tuning the parameters that increase the model generalizability.
Random search is a technique where random combinations of the hyperparameters are used to find the best solution for the built model. The drawback of random search is that it yields high variance during computing. Since the selection of parameters is completely random; and since no intelligence is used to sample these combinations, luck plays its role.


4.How should you maintain a deployed model?

A deployed model needs to be retrained after a while so as to improve the performance of the model. Since deployment, a track should be kept of the predictions made by the model and the truth values. Later this can be used to retrain the model with the new data. Also, root cause analysis for wrong predictions should be done.

5. What are Support Vectors in SVMs?

Support vectors are the data points nearest to the hyperplane, the points of a data set that, if removed, would alter the position of the dividing hyperplane.
Using these support vectors, we maximize the margin of the classifier.
For computing predictions, only the support vectors are used.

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🔥Job Hunting Tip🔥

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Date: 19-10-2023
Company name: IBM
Role: Data Analyst
Topic: Join, OLTP, Joining vs blending, worksheet excel, Python

1. What is a Self-Join?

A self-join is a type of join that can be used to connect two tables. As a result, it is a unary relationship. Each row of the table is attached to itself and all other rows of the same table in a self-join. As a result, a self-join is mostly used to combine and compare rows from the same database table.


2. What is OLTP?

OLTP, or online transactional processing, allows huge groups of people to execute massive amounts of database transactions in real time, usually via the internet. A database transaction occurs when data in a database is changed, inserted, deleted, or queried.


3. What is the difference between joining and blending in Tableau?

Joining term is used when you are combining data from the same source, for example, worksheet in an Excel file or tables in Oracle databaseWhile blending requires two completely defined data sources in your report.


4. How to prevent someone from copying the cell from your worksheet in excel?

If you want to protect your worksheet from being copied, go into Menu bar > Review > Protect sheet > Password.

By entering password you can prevent your worksheet from getting copied.


5.What is map function in Python?

Ans: map function executes the function given as the first argument on all the elements of the iterable given as the second argument. If the function given takes in more than 1 arguments, then many iterables are given.

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Date: 20-10-2023
Company : Tiger Analytics
Role : Data Analyst
Topic : Tableau extract, tableau parameter, freeze pane, vlookup

1. What is a Tableau extract?
A Tableau extract is a compressed file that contains a subset of data from a larger data source. Extracts can be used to improve performance by reducing the amount of data that needs to be loaded into Tableau. Extracts can be created by selecting the "Extract" option when connecting to a data source, and can be refreshed on a schedule or on demand.

2. What is a Tableau parameter?
A Tableau parameter is a dynamic input that allows users to change the behavior of a visualization. Parameters can be used to create dynamic filters, switch between views, or adjust calculations. Parameters are created by defining a data type, range of allowable values, and a default value. Parameters can be used in calculations, filters, and other parts of a Tableau workbook.

3. What is conditional formatting in Excel?
Conditional formatting allows you to apply formatting rules to cells based on specific conditions, such as highlighting values greater than a certain threshold or applying color scales.

4. What is the purpose of the VLOOKUP function in Excel?
The VLOOKUP function is used to search for a value in the leftmost column of a table and retrieve a corresponding value from a different column within the same row.

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🚨30 FREE Dataset Sources for Data Science Projects🔥

US Government Dataset: https://www.data.gov/

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The World Bank Open Data: https://data.worldbank.org/

Data World: https://data.world/

BFI - Industry Data and Insights: https://www.bfi.org.uk/data-statistics

The Humanitarian Data Exchange (HDX): https://data.humdata.org/

Data at World Health Organization (WHO): https://www.who.int/data

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AWS Open Data Registry: https://registry.opendata.aws/

FiveThirtyEight: https://data.fivethirtyeight.com/

IMDb Datasets: https://www.imdb.com/interfaces/

Kaggle: https://www.kaggle.com/datasets

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Google Dataset Search: https://datasetsearch.research.google.com/

Nasdaq Data Link: https://data.nasdaq.com/

Recommender Systems and Personalization Datasets: https://cseweb.ucsd.edu/~jmcauley/datasets.html

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Open Data Network by Socrata: https://www.opendatanetwork.com/

Climate Data Online by NOAA: https://www.ncdc.noaa.gov/cdo-web/

Azure Open Datasets: https://azure.microsoft.com/en-us/services/open-datasets/

IEEE Data Port: https://ieee-dataport.org/

Wikipedia: Database: https://dumps.wikimedia.org/

BuzzFeed News: https://github.com/BuzzFeedNews/everything

Academic Torrents: https://academictorrents.com/

Yelp Open Dataset: https://www.yelp.com/dataset

The NLP Index by Quantum Stat: https://index.quantumstat.com/

Computer Vision Online: http://www.computervisiononline.com/dataset

Visual Data Discovery: https://www.visualdata.io/

Roboflow Public Datasets: https://public.roboflow.com/

Computer Vision Group, TUM: https://vision.in.tum.de/data/datasets

Save It For Later!

Date: 22-10-2023
Company : Accenture
Role : Data Scientist
Topic : Silhouette coeff, Trend&Seasonality, Bag of words, Self join

1. What do you understand by the term silhouette coefficient?
The silhouette coefficient is a measure of how well clustered together a data point is with respect to the other points in its cluster. It is a measure of how similar a point is to the points in its own cluster, and how dissimilar it is to the points in other clusters. The silhouette coefficient ranges from -1 to 1, with 1 being the best possible score and -1 being the worst possible score.

2. What is the difference between trend and seasonality in time series?
Trends and seasonality are two characteristics of time series metrics that break many models. Trends are continuous increases or decreases in a metric’s value. Seasonality, on the other hand, reflects periodic (cyclical) patterns that occur in a system, usually rising above a baseline and then decreasing again.

3. What is Bag of Words in NLP?
Bag of Words is a commonly used model that depends on word frequencies or occurrences to train a classifier. This model creates an occurrence matrix for documents or sentences irrespective of its grammatical structure or word order.

4. What is a Self-Join?

A self-join is a type of join that can be used to connect two tables. As a result, it is a unary relationship. Each row of the table is attached to itself and all other rows of the same table in a self-join. As a result, a self-join is mostly used to combine and compare rows from the same database table.

5.Explain the Law of Large Numbers.

The ‘Law of Large Numbers’ states that if an experiment is repeated independently a large number of times, the average of the individual results is close to the expected value. It also states that the sample variance and standard deviation also converge towards the expected value.

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DATA ENGIINEERING INTERVIEW QNAs

HIVE INTERVIEW QUESTIONS

1.What applications are supported by Hive?

Hive is primarily used for querying and analyzing large datasets stored in Hadoop Distributed File System (HDFS). It is often used for data warehousing, ETL (Extract, Transform, Load) processes, and data analysis. Common use cases include log processing, data aggregation, and data exploration.

2.What are the different types of tables available in Hive?

Hive supports two main types of tables: Managed Tables and External Tables. Managed tables store data in a Hive-specific directory, while external tables reference data stored outside of Hive's control, such as in HDFS or other storage systems.

3.What is the difference between managed and external tables?

Managed tables have their data managed and controlled by Hive. Hive assumes full responsibility for the data's lifecycle, including deleting data when the table is dropped. External tables, on the other hand, don't manage the data themselves and only maintain metadata references to the external data location.

4.Where does the data of a Hive table get stored?

In the case of managed tables, the data is stored in a directory managed by Hive within HDFS. For external tables, the data remains in its original location, and Hive maintains metadata references to it.

5.Can Hive be used in OLTP systems?

Hive is not suitable for OLTP (Online Transaction Processing) systems because it is optimized for batch processing and is not designed for low-latency, high-concurrency transactional operations. OLAP (Online Analytical Processing) workloads are more suitable for Hive.

6.Can a table name be changed in Hive?

Yes, you can rename a table in Hive using the ALTER TABLE statement.

7.Can the default location of a managed table be changed in Hive?

Yes, you can specify a custom location for managed tables during table creation or alter the table to change its location using the LOCATION keyword in the CREATE TABLE or ALTER TABLE statements.

8.What is a Hive Metastore?

The Hive Metastore is a centralized metadata repository in Hive that stores metadata information about tables, partitions, columns, and other objects in the Hive data warehouse. It helps Hive manage and organize data effectively.

9.What are the types of Metastore in Hive?

There are two types of Hive Metastores: Local Metastore, which stores metadata on the local file system, and Remote Metastore, which stores metadata in a separate database like MySQL, PostgreSQL, or Oracle.

10.What is the difference between Local and Remote Metastore?

The key difference is where metadata is stored. Local Metastore stores metadata on the local file system, which is suitable for small-scale setups. Remote Metastore stores metadata in a separate database, making it more scalable and suitable for larger deployments with multiple Hive instances.

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