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Explore what Machine Learning is, why it matters, and where it’s used. Understand the difference between Artificial Intelligence, Machine Learning, and Deep Learning. Learn about types of ML: Supervised, Unsupervised, and Reinforcement Learning.
Learn to collect, clean, and prepare data for ML models. Understand how to handle missing values, outliers, feature scaling, and encoding categorical variables using Python tools like Pandas and NumPy.
Dive deep into algorithms like Linear Regression, Logistic Regression, Decision Trees, Random Forest, and Support Vector Machines. Learn how to build, train, and evaluate these models.
Understand techniques for pattern discovery and grouping without labeled data. Learn clustering techniques such as K-Means, Hierarchical Clustering, and dimensionality reduction with PCA (Principal Component Analysis).
Learn how to measure model performance using evaluation metrics like accuracy, confusion matrix, precision, recall, F1-score, and ROC curves. Understand cross-validation and hyperparameter tuning to improve model accuracy.
Work on projects such as spam email detection, customer segmentation, and stock price prediction. Learn how to deploy ML models for real-world applications and integrate them into business systems or web applications.
The personalized attention I received at Mahendra Academy was amazing. The faculty are highly knowledgeable and always willing to help. I wouldn't have achieved my NEET goals without their guidance.
The study material provided was comprehensive and well-structured. The regular mock tests helped me a lot in managing my time and understanding the exam pattern.
The pre-foundation classes were really helpful in building a strong base for my future studies. The teachers are very supportive and made learning fun!