AI Portfolio
Nov 2022
"PART I: To design and build a CNN classifier capable of determining a flower’s species from a photo
Course: Deep Learning for AI
"PART I : Classification of different species of flowers from their images by making use of CNN concepts. PART II : Sarcasm detection in tweets making use of NLP Concepts."
Skills & Tools Covered
PART 1: Hands-on experience in using Convolution neural networks and transfer learning for building an image classifier. Real-time experience in training
tuning
testing
and comparing an image classifier. PART 2:Hands on experience in importing
pre-processing
and computing a text dataset using python. Realtime experience working on designing
training
and testing sequential NLP classifiers.
Oct 2022
Signal Quality prediction of communication equipment using Neural Networks
Course: Deep Learning for AI
"A communications equipment manufacturing company has a product which is responsible for emitting informative signals.Company wants to build a deep learning model which can help the company to predict the equipment’s signal quality using various parameters."
Skills & Tools Covered
Exploratory Data Analysis and Data Preprocessing
Designing
training
and tuning of Neural Network Model.
Sep 2022
Bank Loan Defaulter Prediction
Course: Advanced Machine Learning
There seems to be no end to bad loans in the country. According to the Reserve Bank of India, the overall badloansasof March 2021 stood at INR 8.35 lakh crore, compared to INR 8.96 lakh crore in March 2020. Banks run into losses when a customer doesn't pay their loans on time. Because of this, every year, bankshavelossesin crores, and this also impacts the country's economic growth to a large extend. In This is project, we will look at various attributes such as funded amount, term, interest rat
Skills & Tools Covered
Feature Selection
Handling Imbalanced data
Hyperparameter Tuning
Building ML Pipelines
Aug 2022
Google Store App Rating Prediction
Course: Advanced Machine Learning
The Play Store apps data has enormous potential to drive app-making businesses to success. However, many apps are being developed every single day and only a few of them become profitable. It is important for developers to be able to predict the success of their app and incorporate features which makes an app successful. We can collect app data and user ratings from the app stores and use it to extract insightful information. A machine learning model can be used to predict rating for a given app
Skills & Tools Covered
Exploratory Data Analysis and Data Preprocessing
Supervised Learning. (Decision Trees
ensemble methods
bagging
boosting and stacking)
Jul 2022
E-commerce Customer Segmentation
Course: Machine Learning
This project is based on the given users and items data of an e-commerce company, segmenting the similar user and items into suitable clusters. Analyzing the clusters and provide your insights to help the organization promote their business
Skills & Tools Covered
Exploratory Data Analysis and Data Preprocessing
Unsupervised Learning
Principal Component Analysis
and Clustering
Jul 2022
Telecom Customer Churn Prediction
Course: Machine Learning
This project is based on building a Supervised Learning Classification model that will help to identify the potential customers who have a higher probability to churn. Then helps the company to understand the pinpoints and patterns of customer churn and will increase the focus on strategizing customer retention.
Skills & Tools Covered
Exploratory Data Analysis and Data Preprocessing
Supervised Learning Classification. (logistic regression
KNN
& Naive Bayes)
Jun 2022
E Commerce Reports with CQL
Course: Databases - SQL and NoSQL
You got a new assignment where you have to keep a track of how customers are liking the products of the company. You are keeping this track by capturing the number of likes against each Product by a customer. Write different types of CQL statements to insert and retrieve data from database.
Skills & Tools Covered
Cassandra
CQL statements
AstraDB
Jun 2022
Travego Travelers
Course: Databases - SQL and NoSQL
Consider there are two table containing details of passengers price to travel between two cities by bus,for types (Sitting and Sleeper). For database storage we will use MySQL. Write different types SQL statements to insert and retrieve specific data from a database. In this project you will be creating first a schema named Travego, and then the two tables mentioned above. You will be also inserting data and retrieving records from table.
Skills & Tools Covered
May 2022
Writing programs to find the routes between specified nodes in graph data structure
Course: Design and Analysis of Algorithms
In this project, a rectangular city area is surrounded by 4 different cities on each of its border. The rectangular city area is comprised of a grid system where altitude of different nodes are stored using python program with the help of graph data structures. The goal is to use graph data structure and perform BFS or DFS to find the route between 2 nodes and the route between 2 cities. Here we are using 2D matrix list to store the data in graph.
Skills & Tools Covered
Graphs
operations on adjacency list graph
2D matrix
list operations
searching techniques
data structures
Apr 2022
Writing programs to find the majority master node in an IoT setup.
Course: Design and Analysis of Algorithms
In this project, an IoT firm has designed a master-slave architecture where multiple sensors are responding to a single master node. These devices have different ID and storage capacity, but the data collected by them is going to a specific master node. The firm has not planned for load balancing. As the number of sensors/devices increased and the firm engineers kept on assigning the devices to a master nodes based on the maximum capacity, it created a unique problem where some of the master nod
Skills & Tools Covered
Lists
divide and conquer algorithm
recursion
Apr 2022
Writing programs to store the power grid data in garph data structure
Course: Data Structures and Algorithms
In this project, a power grid system where data of connected houses with different propagators are stored using python program with the help of graph data structures. The goal is to use graph data structure and perform certain operations such addition, removal of houses and propagators from the designed structure. Here we are using dictionary as an adjacency list to store the data in graph.
Skills & Tools Covered
Graphs
operations on adjacecny list graph
house creation
propogation creation
house removal.
Mar 2022
Writing programs to mimic the Music player system using linked list
Course: Data Structures and Algorithms
In this project, a generic music player system using python program with certain features is implemented. The goal is to use data structure and perform certain operations on the music player where songs are added. Here the implementation consist basic use of OOP and fundamental concepts like sorting, insertion, deletion of the songs from the created playlist.
Skills & Tools Covered
Linked list
operations on linked list
sorting the playlist
shuffling the songs and deletion of the songs.
Jan 2022
Retail Marketing exploratory Data Analysis and Data Preprocessing
Course: Programming with Python
The project is based on exploratory data analysis and data preprocessing methods to understand the marketing campaigns and their outcomes. It involves making use of univariate and bivariate analysis, visualization methods, garbage value treatment, and data manipulation methods to answer queries related to cosumer's purchasing pattern and prepare a report for the management team.
Skills & Tools Covered
Data Visualization
Data Cleaning
Handling missing values
Univariate Analysis
Bivariate Analysis
Seaborn
Python
Jan 2022
Writing programs and analyzing sales data using Python
Course: Programming with Python
The project is based on developing python programs using fundamental concepts like data structures, loops, functions, etc. It also makes use of libraries like pandas and numpy that are used for machine learning. It involves writing programs like checking if an integer is prime or not, calculating the area of a circle, writing function, etc. The project also involves reading sales data, understanding its shape, various features, statistical summary, and performing data manipulation.
Skills & Tools Covered
Python basics
Data structure
Lists
Sets
Loops
Functions
Numpy
Pandas