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This page highlights what I learned in my intense, 6-month AI and machine learning course and how I applied these advanced learning techniques to solve real-world problems. Explore the sections below to learn more on how I transformed complex datasets into actionable insights across various domains.
My AI and ML Journey
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Part 1
Programming, Data Preparation, and Visualization
Learnings
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Mastered foundational Python programming, including working with variables, loops, conditionals, and functions to create efficient, modular code.
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Gained expertise in advanced data manipulation and cleaning using Pandas to build, transform, and analyze DataFrames.
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Integrated APIs to automate data retrieval and processing, streamlining workflows for real-world applications.
Developed impactful data visualization skills with Matplotlib and Pandas, creating clear and insightful plots for effective decision-making. -
Explored time series analysis and forecasting, using tools like Prophet to build predictive models for trends and patterns.
Part 2
Machine Learning and Model Optimization
Learnings
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Applied machine learning techniques to solve practical problems using regression, classification, and clustering models.
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Explored unsupervised learning methods like K-means and PCA for customer segmentation and anomaly detection.
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Built supervised learning models for applications like fraud detection and sales prediction.
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Enhanced model performance with optimization techniques, including cross-validation, hyperparameter tuning, and regularization.
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Addressed imbalanced datasets with resampling techniques (e.g., SMOTE) and built automated machine learning pipelines for efficient and scalable workflows.
Part 3
Advanced AI and Deep Learning Applications
Learnings
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Gained proficiency in neural networks for tasks such as image classification with CNNs and text generation with LSTM models.
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Preprocessed image data and applied data augmentation to improve model training outcomes.
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Mastered NLP techniques, including tokenization, sentiment analysis, and transformers, to handle complex text data challenges.
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Leveraged tools like LangChain and Gemini to build conversational AI applications and Hugging Face for text summarization and question-answering.
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Applied advanced AI technologies and frameworks through hands-on projects, showcasing the ability to implement innovative, industry-ready solutions.
All Certifications
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