I am passionate about exploring and advancing the field of artificial intelligence and machine learning. I focus on building algorithms from scratch, solving real-world problems, and leveraging data-driven insights to design intelligent systems. My journey as an AI researcher/engineer combines theoretical exploration with practical implementation to create impactful solutions.
- AI Algorithms & Foundations: Implementing algorithms like neural networks, decision trees, Naive Bayes, and support vector machines from scratch.
- Deep Learning: Experimenting with architectures such as CNNs, RNNs, and Transformers for tasks in computer vision and natural language processing.
- AI-Driven Problem Solving: Using machine learning to tackle real-world challenges, from data preprocessing to model deployment.
- Research Exploration: Reading papers and learning state-of-the-art techniques like attention mechanisms and reinforcement learning.
- Programming: Python (Intermediate)
- Libraries/Frameworks: NumPy, Pandas, Matplotlib, TensorFlow, PyTorch, Scikit-learn ,Fastai
- Concepts: Supervised/unsupervised learning, optimization techniques, neural networks, natural language processing (NLP), reinforcement learning
- Build innovative AI models and deploy them to solve practical problems.
- Research state-of-the-art advancements in AI and publish my findings.
- Strengthen my understanding of AI mathematics (linear algebra, calculus, probability).
- Create projects showcasing expertise in AI and deep learning applications.
- Neural Network from Scratch: Building a fully connected feedforward neural network with Python.
- AI for Image Classification: Using CNNs to classify datasets such as MNIST and CIFAR-10.
- Natural Language Processing: Sentiment analysis and text generation using Transformer models.
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📫 How to reach me: [email protected]
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⚡ Fun fact: I enjoy exploring the intersection of AI and creativity!
