The Data Project Tracker is an aggregated sheet designed to help students track their projects. It provides a convenient way to organize project details and keep all relevant information in one place.
<aside> đź“Ś Welcome to Data Science and Visualization Training with #datawithmala
These projects are done for the completion of the Data-Science-with-Python-Training
Be sure to share your project on LinkedIn or Instagram and tag us.
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https://github.com/maladeep/Data-Science-with-Python-Training
The tracker includes a table with the following columns:
| SN | Author | Project Title | One line Description | GitHub Link | Presentation Link | |
|---|---|---|---|---|---|---|
| 1 | Ujjwal | EDA on Heart Failure Clinical Records | EDA of Heart Failure Clinical Records involves a comprehensive examination of medical data to uncover patterns, trends, and insights that contribute to a deeper understanding of factors influencing heart failure and patient outcomes. | https://github.com/ub-062/EDA-Of-Heart-Failures-Clinical-Records | ||
| 2 | Ujjwal | EDA on Diabetes Status In India | Exploratory Data Analysis (EDA) on diabetes status in India provides a comprehensive examination of key statistical insights and patterns to better understand the prevalence and factors associated with diabetes in the India. | https://github.com/ub-062/EDA-On-Diabetes-Status-In-India | ||
| 3 | Ujjwal | Presentation on Large Language Model | The Large Language Model presentation project explores the capabilities and applications of advanced natural language processing through an in-depth analysis and demonstration of a state-of-the-art language model. | https://1c1fb-my.sharepoint.com/:p:/g/personal/myfav_1c1fb_onmicrosoft_com/Ed4BwVi_1OVMjofJbCZyz9kB5emLMHTcbhEjhfJp700Tkg?e=8rEsGT | ||
| 4 | Prashna Dhakal | EDA-on-students-examination-performances | This EDA shows multiple relation between the students from various backgrounds and their scores. | https://github.com/dummymummytummy/EDA-on-students-examination-performances | ||
| 5 | Prashna Dhakal | EDA-on-heart-attack-statisics | In this EDA, you can find statistical data on who have been more prone to this infraction. | https://github.com/dummymummytummy/EDA-on-heart-attack-statisics?tab=readme-ov-file#eda-on-heart-attack-statisics | ||
| 6 | Prashna Dhakal | presentation on learning model | learning model presentation revolves around the basic idea of machine learning model and its types. | https://www.canva.com/design/DAF2lnyQ60A/Otgft-NE0ux6neOJ5cKmZg/view | ||
| 7 | Pragyan Shrestha | EDA-on-Stroke-Prediction | In this EDA, you can find the people of different age and their average glucose level | https://github.com/pragyanshresth/An-Analysis-of-Stroke-Prediction | ||
| 8 | Pragyan Shrestha | EDA-on-Car-Dataset | In this EDA, you can find the distance travelled by a car in a certain year | https://github.com/pragyanshresth/An-Analysis-of-Car | ||
| 9 | Pragyan Shrestha | Presentation on Artificial Neural Networking(ANN) | Dive into the world of Neural Networks with this comprehensive introduction, exploring key concepts and applications in this enlightening SlideShare presentation by Databricks. | https://www.canva.com/design/DAF3nIsqWSE/FmBRP7q8_VFxT8zGoJcWYQ/view?utm_content=DAF3nIsqWSE&utm_campaign=designshare&utm_medium=link&utm_source=editor | ||
| 10 | pawan bhattarai | EDA-on-Mall-customers-dataset | The "Mall_Customers.csv" dataset provides demographic and spending information on customers in a shopping mall, including features such as CustomerID, Gender, Age, Annual Income, and Spending Score. | https://github.com/Pawan-Bhattarai-609/eda-on-mall-customers-data-set | ||
| 11 | pawan bhattarai | EDA-on-Auto-sales-dataset | The "autosales_data.csv" dataset captures information on auto sales, encompassing details on car prices, brands, and features, enabling exploratory data analysis to uncover trends and patterns within the automotive market. | https://github.com/Pawan-Bhattarai-609/eda-on-autosales-data/tree/main | ||
| 12 | pawan bhattarai | presentation on deepfake | The "Deepfake.pptx" presentation explores the phenomenon of deepfakes, providing insights into the technology's implications, detection methods, and potential societal impact in the realm of manipulated audiovisual content. | https://www.slideshare.net/prokillnofan/deepfakeppppppppppppppppppppppppppppppppppppppppppt | ||
| 13 | Aayush Poudel | Presentation on Reinforcement Learning | In this reinforcement learning project, an autonomous agent is trained to navigate a complex environment, making sequential decisions to optimize its behavior and achieve specific objectives through the iterative process of learning from rewards and interactions. | https://www.slideshare.net/aayushpoudel2602/presentation-on-reinforcement-learningpdf | ||
| 14 | Aayush Poudel | Exploratory Data Analysis (EDA)-Life Expectancy | In this Exploratory Data Analysis (EDA) project on life expectancy, we analyze and uncover insights from diverse factors influencing life expectancy, utilizing statistical and visual exploration of the dataset. | https://github.com/Aayush-Poudel1/EDA-1-LIFE-EXPENTENCY/tree/main | ||
| 15 | Aayush Poudel | Exploratory Data Analysis | ||||
| (EDA)- Food Dataset | In this Exploratory Data Analysis (EDA) project on a food dataset, we delve into comprehensive analysis and visualization to gain insights into nutritional patterns, dietary trends, and key factors influencing food choices, providing a nuanced understanding of the dataset. | https://github.com/Aayush-Poudel1/EDA-2-FOOD | ||||
| 16 | Prasis Gautam | Exploratory Data Analysis | ||||
| (EDA)- Heart Attack Prediction | The EDA in the "EDA-of-Heart-Attack-Prediction" GitHub repository involves exploring, cleaning, analyzing, and visualizing heart-related dataset variables to understand patterns and potentially build predictive models for heart attack occurrences. | https://github.com/PrasisGautam/EDA-of-Heart-Attack-Prediction | ||||
| 17 | Prasis Gautam | Exploratory Data Analysis | ||||
| (EDA)- Unemployment Rate Analysis | This repository contains the code and dataset used for the Exploratory Data Analysis (EDA) of Unemployment Rate Analysis. The analysis aims to explore the dataset, understand unemployment trends, and derive insights that might contribute to understanding factors affecting unemployment rates. | https://github.com/PrasisGautam/EDA-of-Unemployment-Rate-Analysis | ||||
| 18 | Prasis Gautam | Presentation on GAN for image generation | This presentation illustrates the principles and application of Generative Adversarial Networks (GANs), showcasing their role in generating images through advanced artificial intelligence techniques. | https://www.canva.com/design/DAF2xen_jDQ/DnSlCOqD5F7xchvqSGXSxQ/view | ||
| 19 | Sangam BK Thapa | Exploratory | ||||
| 20 i. | Rasik Dhakal | Exploratory Data Analysis | ||||
| (EDA)- | ||||||
| Agricultural Renaissance: Analyzing the Patterns of Increasing Crop Yields | EDA to find the general trend of crop production over time by analyzing historical data, understanding the patterns, identifying potential influencing factors, and providing valuable insights for sustainable agricultural planning and policy formulation. | https://github.com/LAKAHDKISAR/Agricultural-Renaissance_Analyzing-the-Patterns-of-Increasing-Crop-Yields | ||||
| 21 ii. | Rasik Dhakal | Exploratory Data Analysis | ||||
| (EDA)- | ||||||
| Coffee Flavor EDA | This EDA explores the fascinating world of coffee flavors by uncovering patterns, trends, and interesting insights related to various aspects of coffee flavor profiles, with the main objective of finding out how the altitude of the region where the coffee beans are produced affects the flavor of the coffee.**** | https://github.com/LAKAHDKISAR/Coffee-Flavor-EDA | ||||
| 22 iii. | Rasik Dhakal | The Future of GANs: Innovations and Emerging Trends | The presentation on the topic “The Future of GANs: Innovations and Emerging Trends “ explores the fascinating world of GANs and is divided into 5 parts those being: Introduction, Operational Methodology, Applications and Emerging Trends, Innovation, and finally the future potential of GANs. | https://www.canva.com/design/DAF2xTBe6vI/BuaERq9ZcIqD4V8JRQUC-w/edit?utm_content=DAF2xTBe6vI&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton | ||
| 23. | Prathama Shrestha | Exploratory Data Analysis on Global Data Science Salaries | The data analysis delves into comprehensive insights and visualizations, examining the intricate landscape of global data science salaries. Through statistical exploration and graphical representation, the project aims to correlate the salary, experience level and job type within the dynamic field of data science across different regions. | https://github.com/prathama7/EDA-of-Global-Data-Science-Salaries | ||
| 24. | Prathama Shrestha | Exploratory Data Analysis on Employee Dataset | The EDA conducts in-depth analysis and visualization to unveil meaningful patterns, trends, and insights within the employee dataset, majorly including the age, gender, education and experience providing valuable perspectives on workforce dynamics. | https://github.com/prathama7/EDA-of-Employee-Dataset | ||
| 25. | Prathama Shrestha | Understanding Large Language Model | “Understanding Large Language Model” involves a comprehensive journey into the intricacies of cutting-edge artificial intelligence. This exploration encompasses the architecture, working, benefits, challenges and impact of models like GPT-3, shedding light on their capacity to understand and generate human-like language patterns. Dive into the evolving landscape of these models, unraveling their potential impact on natural language processing, creativity, and the broader landscape of AI-driven advancements. | https://www.canva.com/design/DAF2xRE7AFk/7lhLFYJCsh0nD3gsqdDMlg/edit?utm_content=DAF2xRE7AFk&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton | ||
| 26. | Surasa Silpakar | EDA on Student Mental Health | "EDA on Student Mental Health" conducts a thorough examination of data related to students' mental well-being, uncovering patterns and correlations in factors like academic stress, social interactions, and lifestyle. This analysis aims to identify key insights, potential risk factors, and inform targeted interventions for better supporting student mental health and overall success in education. | https://github.com/surasa-s/EDA-Student-Mental-Health | ||
| 27. | Surasa Silpakar | EDA on Future50 Restaurants | EDA on the Future 50 Restaurants highlights cutting-edge eateries redefining dining with innovative menus and sustainable practices that explores a curated list of culinary trailblazers shaping the future of food culture. | https://github.com/surasa-s/Future50 | ||
| 28. | Surasa Silpakar | Understanding Large Language Models | Understanding Large Language Models explores the capabilities, architecture, and ethical implications of advanced AI systems like GPT models. Delving into their potential applications and limitations, this analysis sheds light on the impact of large language models in fields like natural language processing and AI ethics. | https://www.canva.com/design/DAF2xRE7AFk/7lhLFYJCsh0nD3gsqdDMlg/edit?utm_content=DAF2xRE7AFk&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton | ||
| 29. | Sugat Shakya | EDA on World Happiness Report | Conducted exploratory data analysis (EDA) on the World Happiness Report to unveil insights into global well-being trends and factors influencing happiness.” | https://github.com/sugaat/EDA-Happiness-Report-with-frontend | ||
| Sugat Shakya | EDA on Shopping Trends | Conducting EDA on shopping trends for actionable insights in retail decision-making | https://github.com/sugaat/EDA-Shopping-Trends | |||
| Sugat Shakya | The Future of Gans: Innovation and Emerging Trends | Unveiling the power of GANs in AI and creativity in this presentation. | https://www.slideshare.net/SugatShakya5/the-future-of-gans-innovation-and-emerging-trends | |||
| 30 | Kritika Silwal | EDA on Cosmetics | "EDA-on-Cosmetics, for performing Exploratory Data Analysis on cosmetic-related datasets. The repository likely explores and analyzes various aspects of cosmetic data, providing insights and visualizations to better understand patterns and trends within the dataset. | https://github.com/kritika-silwal/EDA-on-Cosmetics | ||
| Kritika Silwal | An Analysis on Lungs Cancer | The EDA on Lungs Cancer deals with the provided information which includes age of smokers and the risk of them having high chances of lungs cancer. | https://github.com/kritika-silwal/An-Analysis-on-Lung-Cancer | |||
| Kritika Silwal | Presentation on Artificial Neural Networking(ANN) | Artificial Neural Networks (ANN) typically involves summarizing the model's performance and its ability to learn complex patterns from data. It may include insights into the network's strengths, weaknesses, and its overall effectiveness in solving the specific problem it was designed for. Evaluation metrics such as accuracy, precision, recall, and F1 score may be considered, along with any potential areas for improvement or future work. | https://www.canva.com/design/DAF3nIsqWSE/FmBRP7q8_VFxT8zGoJcWYQ/view?utm_content=DAF3nIsqWSE&utm_campaign=designshare&utm_medium=link&utm_source=editor | |||
| 31 | Rij Amatya | EDA on titanic disaster survival | The exploration of the Titanic dataset looked at different details like passenger class, age, gender, and ticket prices using graphs and numbers to see if there were any connections between these things and who survived making sure what affected their chances of making it through the disaster. | https://github.com/rijamatya/Survival-during-Titanic-disaster | ||
| 32 | Rij Amatya | EDA on Student Grade Prediction | In this EDA, various factors like study time, previous grades, attendance, and extracurricular activities, aspects of student life which might impact their academic performance, helping educators tailor support were analyzed using charts and statistics to understand if these factors influenced students future grades. | https://github.com/rijamatya/Student-Grade-Prediction-Analysis | ||
| 33 | Rij Amatya | Presentation on ANN (Artificial Neural Networking) | Starting with the basic introduction, this presentation includes the working of ANN and its rule in 21st century with applications where BNN is compared to ANN. | https://www.canva.com/design/DAF3nIsqWSE/FmBRP7q8_VFxT8zGoJcWYQ/view?utm_content=DAF3nIsqWSE&utm_campaign=designshare&utm_medium=link&utm_source=editor | ||
| 34 | Omraj Budhatohki | The Future of Gans: Innovation and Emerging Trends | This presentation "The Future of GANs: Innovations and Emerging Trends" delves into the captivating realm of GANs and is structured into five sections: Introduction, Operational Methodology, Applications and Emerging Trends, Innovation, and the prospective advancements of GANs. | https://www.slideshare.net/secret/zPZfcOH58vnuTt | ||
| 35 | Omraj Budhatohki | EDA on smoking | Exploratory Data Analysis (EDA) on smoking entails the comprehensive examination and interpretation of smoking-related data to uncover patterns, trends, and insights. | https://github.com/OmrajBudhathoki/Eda.git | ||
| 36 | Omraj Budhathoki | EDA on bodyfat | Exploratory Data Analysis (EDA) on body fat involves the thorough investigation and interpretation of body fat-related data to reveal correlations, distributions, and key insights. | https://github.com/OmrajBudhathoki/Eda.git | ||
| 37 | Pritam Budhathoki | WorkShop EDA | Exploratory Data Analysis(EDA) on workshop for olympic athlete overall status. | https://github.com/PritamBudhathoki/EDA-Project | ||
| 38 | Biplove Kharel ,Prajwol paudel and Pritam Budhathoki | Powerpoint Presentation on Clustering and LLMs | In this presentation, The total problems related to Clustering during LLMs in included. The full description is given. | C:\Users\asus\Documents\clustering.pptx | ||
| 39 | Biplove Kharel | EDA on healthcare | This includes EDA on the data of health status of human population. | https://github.com/biplove7/biplove7/blob/main/eda1.docx | ||
| 40. | Prajwol Paudel | EDA on sports | This includes comparing the stat of the IPL player | https://github.com/Mambax60/EDA-on-IPL.git |
Remember
<aside> 👉 Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.
― Antoine de Saint-Exupéry
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