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Notes and codes on AI/ML topics
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anandsaha/my.ai.ml.lab
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{
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"# AI and Machine Learning algorithm notes\n",
"\n",
"### Supervised algorithms\n",
"\n",
"\n",
"\n",
"|Sr.No.| Algorithm | Classification | Regression | Notes |\n",
"|------|:--------------------------------------|:--------------:|:----------:|------------------|\n",
"|1 |Naive Bayes | Yes | No | - |\n",
"\n",
"\n",
"\n",
"\n",
"1. [Naive Bayes (Using Gaussian NB) for Classification](ml_naive_bayes.ipynb)\n",
"2. Support Vector Machines (SVM) for Classification\n",
"3. Decision Tree for Classification and Regression\n",
"4. K Nearest Neighbours for Classification and Regression\n",
"5. AdaBoost for Classification (in conjunction with Decision Tree)\n",
"6. Random Forest\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
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"source": [
"## Unsupervised Algorithms\n",
"\n",
"Used to learn clusters of probability distribution of data\n",
"\n",
"### Clustering\n",
"\n",
"1. K Means Clustering\n",
"2. Hierarchial Clustering\n",
"3. Gaussian Mixture Models, Probability Density Estimation (Under certain conditions, this is same as K Means)"
]
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