feat: add Non-overlapping Intervals explanation

- Greedy algorithm approach
- Comprehensive problem analysis
- Multiple approaches and optimizations
- Edge cases and applications

Author: TechnoBlogger14o3

neetcode-150/intervals/non-overlapping-intervals/explanation.md

@@ -0,0 +1,79 @@
+# Non-overlapping Intervals
+
+## Problem Statement
+
+Given an array of intervals `intervals` where `intervals[i] = [starti, endi]`, return the minimum number of intervals you need to remove to make the rest of the intervals non-overlapping.
+
+## Examples
+
+**Example 1:**
+```
+Input: intervals = [[1,2],[2,3],[3,4],[1,3]]
+Output: 1
+Explanation: [1,3] can be removed and the rest of the intervals are non-overlapping.
+```
+
+## Approach
+
+### Method 1: Greedy Algorithm (Recommended)
+1. Sort intervals by end time
+2. Use greedy approach to select non-overlapping intervals
+3. Count removed intervals
+4. Most efficient approach
+
+**Time Complexity:** O(n log n) - Sorting
+**Space Complexity:** O(1) - In-place modification
+
+### Method 2: Dynamic Programming
+1. Use DP to find maximum non-overlapping intervals
+2. Return total - maximum
+3. Less efficient than greedy approach
+
+**Time Complexity:** O(n²) - Nested loops
+**Space Complexity:** O(n) - DP array
+
+## Algorithm
+
+```
+1. Sort intervals by end time
+2. Initialize count = 0, end = intervals[0][1]
+3. For i from 1 to n-1:
+   a. If intervals[i][0] < end: count++
+   b. Else: end = intervals[i][1]
+4. Return count
+```
+
+## Key Insights
+
+- **Greedy Choice**: Always select interval with earliest end time
+- **Local Optimum**: Maximum non-overlapping intervals
+- **Global Optimum**: Minimum intervals to remove
+- **Space Optimization**: Use only necessary space
+
+## Alternative Approaches
+
+1. **Dynamic Programming**: Use DP for maximum intervals
+2. **Sorting by Start**: Sort by start time and use different logic
+3. **Brute Force**: Try all possible combinations
+
+## Edge Cases
+
+- Empty intervals: Return 0
+- Single interval: Return 0
+- No overlaps: Return 0
+- All overlaps: Return n-1
+
+## Applications
+
+- Interval algorithms
+- Scheduling problems
+- Algorithm design patterns
+- Interview preparation
+- System design
+
+## Optimization Opportunities
+
+- **Greedy Algorithm**: Most efficient approach
+- **Space Optimization**: O(1) space complexity
+- **Logarithmic Time**: O(n log n) time complexity
+- **No Extra Space**: Use only necessary space