Skip to content
View dhyeysavalia01's full-sized avatar
🔥
Ablaze
🔥
Ablaze
5 followers · 11 following

Achievements

Achievement: QuickdrawAchievement: Pull Shark

Achievements

Achievement: QuickdrawAchievement: Pull Shark

Block or report dhyeysavalia01

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
dhyeysavalia01/README.md

Dhyey Savaliya

Machine Learning Enthusiast

LinkedIn · Email · Resume

# ================================
# 🔹 CORE PROFILE
# ================================
class DhyeySavaliya:
    def __init__(self):
        self.name = "Dhyey Savaliya"
        self.education = "B.Tech CSE @ MIT-WPU, Pune"
        self.cgpa = 7.75
        self.current_role = "Intern at SAC-ISRO"

    # ================================
    # 🧠 TECH STACK
    # ================================
    def tech_stack(self):
        return {
            "programming_languages": ["Python", "C++"],
            "machine_learning": [
                "NumPy",
                "Pandas",
                "Matplotlib",
                "Seaborn",
                "Scikit-learn"
            ],
            "databases": ["MySQL"],
            "tools_and_platforms": [
                "Git",
                "GitHub",
                "Jupyter Notebook",
                "Tableau"
            ]
        }

    # ================================
    # 📊 RESEARCH & PROJECTS
    # ================================
    def research_and_projects(self):
        return {
            "Atmospheric CO₂ Forecasting": {
                "best_model": "LSTM",
                "evaluation_metrics": {
                    "RMSE": 0.8750,
                    "MAE": 0.6739
                }
            },
            "Satellite Signal Classification": {
                "model": "Decision Tree",
                "accuracy": "87.9%"
            },
            "Diabetes Risk Prediction": {
                "model": "Logistic Regression",
                "accuracy": "77%"
            }
        }

    # ================================
    # 🏆 ACHIEVEMENTS
    # ================================
    def achievements(self):
        return [
            "🥉 3rd Place — HackMITWPU’24 Ideathon (Healthcare ML)"
        ]

力

Pinned Loading

  1. Healthcare-Patient-Risk-and-Readmission-Analytics Healthcare-Patient-Risk-and-Readmission-Analytics Public

    Built an end-to-end analytics pipeline on 5,000 patient records — SQL for querying and cleaning, a Random Forest model (0.74 ROC-AUC) to score readmission risk, and an interactive Tableau dashboard…

    Python

  2. Olympic-athletes-data-analysis Olympic-athletes-data-analysis Public

    Performed end-to-end exploratory data analysis on a real-world athlete dataset by validating data quality (duplicate records), designing decade-wise temporal aggregations, and visualizing long-term…

    Jupyter Notebook

  3. Satellite-Signal-Strength-Classification Satellite-Signal-Strength-Classification Public

    Created an ML pipeline to classify satellite signal strength using telemetry data, improving communication reliability assessment. Achieved 81.2%, 87.9%, and 81.2% accuracies for KNN, Decision Tree…

    Jupyter Notebook

  4. ML-Diabetes-Prediction ML-Diabetes-Prediction Public

    Built preprocessing pipelines and an interface for professionals to assess diabetes risk accurately. Accuracy of 77% for Logistic Regression model.

    Jupyter Notebook

  5. Machine-Learning Machine-Learning Public

    Jupyter Notebook