Add Seed-Based Ensemble Notebook and Mosquito Trajectory Prediction Scripts

- Created a new Jupyter notebook for seed-based ensemble modeling, including data preprocessing, model training, and weighted averaging ensemble techniques.
- Added README for the mosquito trajectory prediction competition, detailing the problem statement, evaluation metrics, and data structure.
- Implemented a training and submission script for mosquito trajectory forecasting using a stacked ensemble approach with motion priors and residual models.
- Introduced a new notebook demonstrating numpy dot product operations for weighted averaging and matrix multiplication.

Author: hundong2

dacon/8.1.2.Ensemble_Example.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "76864e35",
    "metadata": {},
    "outputs": [
@@ -21,7 +21,7 @@
    "source": [
     "import numpy as np\n",
     "from sklearn.datasets import make_classification\n",
-    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.model_selection import train_test_splitfit_transform\n",
     "from sklearn.metrics import accuracy_score\n",
     "from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier\n",
     "from sklearn.linear_model import LogisticRegression\n",