Anirban Banerjee
Software Engineering
Summary
Good skilled software development professional bringing enormous talents for software design, development and integration. Offering advanced knowledge of Java, JavaScript, Oops, SQL programming languages and basic of AJAX. Background writing code and developing systems for Software applications. Hardworking and passionate job seeker with strong organizational skills eager to secure entry-level Software Developer position. Ready to help team achieve company goals.
Overview
1
1
Certification
3
3
Languages
Work History
Software Developer
LabVantage Solutions
Kolkata
7 2022 - Current
- Deliver software solutions that precisely meet customer's specifications and requirements.
- Integrated third-party APIs to enhance application features and capabilities, broadening product offerings.
- Improved software efficiency by troubleshooting and resolving coding issues.
- Saved time and resources by identifying and fixing bugs before product deployment.
- Updated old code bases to modern development standards, improving functionality.
- Discussed issues with team members to provide resolution and apply best practices.
- Contributed to positive team environment through effective communication, problem-solving, and collaboration skills
- Analyzed work to generate logic for new systems, procedures and tests
- Contributed ideas and suggestions in team meetings and delivered updates on deadlines, designs, and enhancements
Education
10th -
Bankura Zilla School
Bankura, IndiaB.Tech/B.E. -
Techno India Group
Kolkata, West Bengal05.2022
12th -
Rajaram Vivekananda Hindu Vidyalaya
Bankura, India02.2018
Skills
Algorithms
Data Structures
SQL
DBMS
Core Java
C
OOPS
SQL Databases
Technical Skills
- Oracle SQL
- Java
- Ajax
- Javascript
- JBoss EAP
- SQL Server
Personal Information
- Date of Birth: 11/03/99
- Gender: Male
Projects
Prediction and Classification of Cardiac Arrhythmia using Machine Learning, Irregularity in heart beat may be harmless or life threatening. Hence both accurate detection of presence as well as classification of arrhythmia are important. Arrhythmia can be diagnosed by measuring the heart activity using an instrument called ECG or electrocardiograph and then analysing the recorded data. Different parameter values can be extracted from the ECG waveforms and can be used along with other information about the patient like age, medical history, etc. to detect arrythmia. However, sometimes it may be difficult for a doctor to look at these long duration ECG recordings and find minute irregularities. Therefore, using machine learning for automating arrhythmia diagnosis can be very helpful. The project aims at using different machine learning algorithms like Naive Bayes, SVM, Random Forests and Neural Networks for predicting and classifying arrhythmia into different categories.
Certification
Java Training - Sep 2022
Hobbies
My hobbies include playing cricket and football, solving problems, and cooking.
Timeline
Java Training - Sep 2022
09-2022
Software Developer
LabVantage Solutions
7 2022 - Current
10th -
Bankura Zilla School
B.Tech/B.E. -
Techno India Group
12th -
Rajaram Vivekananda Hindu Vidyalaya
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