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108 | 108 | " - [x] ☑️Understand the requirements<br><br>\n",
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109 | 109 | "- [x] [2] ✅ [<ins> Data Collection</ins>](https://github.com/users/iPoetDev/projects/22/views/1?pane=issue&itemId=72909298)\n",
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110 | 110 | " - [x] ☑️Gather Relevant Data - Kaggle\n",
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111 |
| - " - [?] ❌Ensure Data diversity\n", |
112 |
| - " - [?] ❌Prioritize quality sources <br><br>\n", |
| 111 | + " - [?] ☑️Ensure Data diversity\n", |
| 112 | + " - [?] ☑️Prioritize quality sources <br><br>\n", |
113 | 113 | "- [x] [3] ✅[<ins> Data Processing</ins>](https://github.com/users/iPoetDev/projects/22?pane=issue&itemId=72909353)\n",
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114 | 114 | " - [x] ☑️Clean the data\n",
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115 |
| - " - [?] ❌Organize information - Pre organised\n", |
| 115 | + " - [?] ↪️Organize information - Pre organised\n", |
116 | 116 | " - [x] ☑️Visuaise Format for analysis <br><br>\n",
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117 | 117 | "- [ ] [4] ✅[<ins> Algorithm Selection</ins>](https://github.com/users/iPoetDev/projects/22#)\n",
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118 | 118 | " - [x] ☑️Choose appropriate models\n",
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121 | 121 | "- [x] [5] ✅ [<ins> Model Training</ins>](https://github.com/users/iPoetDev/projects/22?pane=issue&itemId=72916346)\n",
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122 | 122 | " - [x] ☑️Feed data into model | split the data\n",
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123 | 123 | " - [x] ☑️Adjust Parameters\n",
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124 |
| - " - [?] ❌Optimize performance <br><br>\n", |
| 124 | + " - [?] ❓Optimize performance <br><br>\n", |
125 | 125 | "- [x] [6] ✅ [<ins>Testing and Validation</ins>](https://github.com/users/iPoetDev/projects/22?pane=issue&itemId=72916473)\n",
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126 | 126 | " - [x] ☑️Assess model accuracy\n",
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127 |
| - " - [?] ❌Cross Validate Results\n", |
128 |
| - " - [?] ❌Ensure reliability <br><br>\n", |
| 127 | + " - [?] 🛑Cross Validate Results\n", |
| 128 | + " - [?] 🛑Ensure reliability <br><br>\n", |
129 | 129 | "- [ ] [ 7] ❌ [<ins> Iteration and Improvement </ins>](https://github.com/users/iPoetDev/projects/22?pane=issue&itemId=72917451)\n",
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130 |
| - " - [?] ❌Refine algorithms (selection, or logic)\n", |
131 |
| - " - [?] ❌Enhance data quality (sourcing, composition)\n", |
132 |
| - " - [?] ❌Optimize parameters (weights, biases)\n", |
| 130 | + " - [?] 🛑Refine algorithms (selection, or logic)\n", |
| 131 | + " - [?] 🛑Enhance data quality (sourcing, composition)\n", |
| 132 | + " - [?] 🛑Optimize parameters (weights, biases)\n", |
133 | 133 | "\n",
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134 | 134 | "> <hr>\n",
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135 | 135 | "\n",
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169 | 169 | "source": [
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170 | 170 | "## 3. Methods & Approaches\n",
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171 | 171 | "\n",
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172 |
| - "-" |
| 172 | + "- Follow Live Technical Session\n", |
| 173 | + "- Email support from IBM Skills Build" |
173 | 174 | ],
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174 | 175 | "metadata": {
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175 | 176 | "id": "kyLJToeRNIJq"
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286 | 287 | "## 5. Solution\n",
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287 | 288 | "\n",
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288 | 289 | "- Coding Style: Employ Functions for completness and future testing\n",
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289 |
| - "- Test Function input for type errors / exit funtion.\n", |
| 290 | + "- Test Function input for type errors / exit function.\n", |
| 291 | + "- Drop custom function back to procedural/top level when error happen (simplify)\n", |
| 292 | + "- Use NumpY Dosstrings to document each custom function. Great to provide in code context/addtional notes.\n", |
| 293 | + "- Constants for top level control params .\n", |
| 294 | + "- Check for types / type errors for inbound parameters.\n", |
290 | 295 | "\n",
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291 | 296 | "\n",
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292 | 297 | "## Importing Necessary Libraries"
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