Intel OneAPI Project
I had Developed a Project for my Intel OneAPI Hackathon Second Round i.e. Submission Round
We harnessed OneAPI's versatile framework to optimize our machine learning model. This ensured efficient utilization of available resources. To speed up training, we used Intel's DevCloud, a cloud-based environment, to distribute workloads across multiple CPUs and GPUs, reducing training time through parallel processing.
These machine learning and deep learning frameworks are used to develop and train models that classify a child's growth status based on collected data. These frameworks provide a wide range of tools, algorithms, and pre-trained models that can be fine-tuned for accurate classification.
Android Studio with Java is a powerful combination for developing Android applications. Android Studio is the official integrated development environment (IDE) for Android app development, providing a comprehensive set of tools and resources to streamline the development process. Java, a widely-used programming language, serves as the primary language for Android app development, offering reliability and versatility while adding functionality to the Application( as backend language).
Firebase, played a crucial role in enhancing the app's functionality. Firebase Realtime Database allowed for seamless data synchronization across devices in real-time, enabling users to access and share information effortlessly. Firebase Authentication provided a secure and hassle-free way for users to log in and interact with the app's features while maintaining their privacy.
In this project, we will utilise web scraping techniques using Python, specifically leveraging the BeautifulSoup library. Our objective is to extract government schemes from the official website while prioritising security and authentication. To achieve this, we will employ technologies such as Requests for making HTTP requests and other essential libraries to facilitate the scraping process
The app can leverage advanced machine learning algorithms to continuously improve its predictive capabilities. By analysing a larger dataset and incorporating more complex variables, the accuracy of the predicted scores and loan eligibility can be enhanced, providing users with more reliable information.
Collaborating with financial institutions and credit rating agencies can enable the app to integrate credit scoring models into its algorithms. This integration would provide users with a more accurate assessment of their creditworthiness and increase their chances of obtaining loans from traditional lenders.
Developing robust algorithms to match skilled individuals with suitable job opportunities is crucial. The app can leverage comprehensive skill databases, job market trends, and user preferences to provide personalized job recommendations that align with the users' skills and qualifications.
The app can expand its analysis of the job market by incorporating real-time data on job openings, industry demands, and emerging sectors. This information can help users identify high-demand skill sets and explore potential career paths, maximizing their chances of finding suitable employment.
Including networking and mentorship features within the app can facilitate connections between skilled individuals and industry professionals. This platform can provide guidance, advice, and mentorship opportunities to economically weak individuals, enabling them to expand their professional networks and gain valuable insights into their desired fields.
Encouraging users to provide feedback and reviews on their experiences with the app can help identify areas for improvement and enhance user satisfaction. This feedback can inform future updates and features, ensuring the app meets the evolving needs of its users.
Collaborating with training programs and non-governmental organisations (NGOs) can provide economically weak individuals with access to skill development programs, educational resources, and job placement assistance. These partnerships can be integrated into the app, expanding the range of opportunities available to users and increasing their chances of success.
Adapting the app to different regions and providing multilingual support can make it more accessible to a wider user base. This localization effort would enable individuals from diverse socioeconomic backgrounds to benefit from the app's services, promoting inclusivity and addressing specific regional challenges.
By incorporating these future improvements, the app can empower economically weak individuals by providing accurate predictions of loan eligibility, personalised job recommendations, networking opportunities, and access to skill development resources. This holistic approach will contribute to bridging the gap between skills and opportunities, fostering socio-economic growth and empowerment