| Sr. No. | Title | Author | PDF |
| 1 | Unsupervised Algorithm: K – means | Soham Dahanukar | PDF |
| 2 | Machine Learning in Independent Vehicles: Exploring Challenges and Developments | Jagruti Borse | PDF |
| 3 | Unlocking Insights with Linear Regression: A Fundamental Tool in Data Analysis | Neha Singh | PDF |
| 4 | Random Forests: A Versatile Ensemble Learning Approach | Hemani Maurya | PDF |
| 5 | Ensuring Equity in Machine Learning: Strategies for Mitigating Bias and Promoting Fairness | Yash Biranje | PDF |
| 6 | Machine Learning in Healthcare: Transforming Patient Care with Data | Amulya Shetty | PDF |
| 7 | Machine Learning Hardware: GPUs, TPUs, and Beyond | Aryan Singh Rawat | PDF |
| 8 | Support Vector Machine (SVM) | Shristi Kamble | PDF |
| 9 | Practical Examples of Machine Learning in Daily Life | Shalaka Kadam | PDF |
| 10 | Anomaly Detection : Identifying Outliers and Anomalies in Data | Shruti Pawar | PDF |
| 11 | You Need to Get Yourself a PrivateGPT Right Now!!!! | Aditya Biradar | PDF |
| 12 | Cancer Classification through Logistic Regression in Machine Learning | Hardik Raut | PDF |
| 13 | Principal Component Analysis for Dimensionality Reduction in Machine Learning | Prerna Mhatre | PDF |
| 14 | Natural Language Processing (NLP) | Manasvi Todkar | PDF |
| 15 | Introductory Guide to Decision Trees: Solving Classification Problems | Aadil Shaikh | PDF |
| 16 | Bias and Variance | Yatin Chauhan | PDF |
| 17 | Exploring the World of Reinforcement learning | Samit Malap | PDF |
| 18 | Understanding Key Performance Metrics for Regression Models | Devharsh Jha | PDF |
| 19 | Ethical Considerations in Machine Learning: Addressing Bias and Fairness | Raghvendra Devadiga | PDF |
| 20 | Understanding Underfitting and Overfitting in Machine Learning | Smit Padsala | PDF |
| 21 | Convolutional Neural Networks (CNNs) | Sanket Das | PDF |
| 22 | Multi-Layer Perceptron Networks | Parth Raut | PDF |
| 23 | Artificial Neural Networks | Ojasi Prabhu | PDF |
