class SuryanshSingh:
def __init__(self):
self.name = "Suryansh Singh"
self.role = "AI/ML Engineer | Python Developer"
self.education = "B.Tech Computer Science & Engineering"
self.graduation = 2028
self.location = "Roorkee, India"
self.core_stack = [
"Python",
"SQL & PostgreSQL",
"Machine Learning",
"Deep Learning",
"Natural Language Processing",
"Data Analysis"
]
self.tools = [
"Pandas",
"NumPy",
"Scikit-learn",
"TensorFlow",
"Keras",
"Streamlit",
"Git & GitHub"
]
self.goal = "Build Production Ready AI Systems."
me = SuryanshSingh()
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End-to-end ML classification project with a Streamlit interface. ✔ Data Preprocessing ✔ EDA & Feature Engineering ✔ Classification ✔ Model Evaluation Tech: Python • Pandas • Scikit-learn • Streamlit
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NLP-based emotion classification system with a Streamlit application. ✔ Text Preprocessing ✔ TF-IDF / Bag of Words ✔ Text Classification ✔ Probability-based Prediction Tech: Python • NLTK • Scikit-learn • Streamlit
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Machine learning regression project for predicting used car prices. ✔ Data Analysis ✔ Feature Engineering ✔ Regression ✔ Model Evaluation Tech: Python • Pandas • NumPy • Scikit-learn
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Regression project for estimating medical insurance costs. ✔ Data Cleaning ✔ EDA ✔ Regression Modeling ✔ Model Evaluation Tech: Python • Pandas • NumPy • Scikit-learn
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Deep learning project comparing a Perceptron, ANN, and CNN on handwritten digit classification. ✔ Image Preprocessing ✔ ANN ✔ CNN ✔ Model Comparison ✔ Confusion Matrix Tech: Python • TensorFlow • Keras • NumPy • Matplotlib 
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| Certification | Issuing Organization | Skills |
|---|---|---|
| Data Visualization | Tata Group — Forage | Effective Insights & Storytelling |
| Data Analytics | Deloitte Australia — Forage | Data Analytics Job Simulation |
| Machine Learning | MindLuster | Supervised & Unsupervised ML |
| Python Programming | MindLuster | Python Fundamentals & OOP |
| Statistics for Data Science | MindLuster | Descriptive & Inferential Statistics |
| Pandas & NumPy | MindLuster | Data Manipulation & Numerical Computing |
graph LR
A[Python] --> B[Data Analysis]
B --> C[Machine Learning]
C --> D[SQL]
D --> E[NLP]
E --> F[Deep Learning]
F --> G[Computer Vision]
G --> H[MLOps]
style A fill:#2563EB,color:#fff
style B fill:#0EA5E9,color:#fff
style C fill:#38BDF8,color:#fff
style D fill:#F7931E,color:#fff
style E fill:#4CAF50,color:#fff
style F fill:#FF6F00,color:#fff
style G fill:#7C3AED,color:#fff
style H fill:#F43F5E,color:#fff