diff --git a/2019-spring/Assignment-02.ipynb b/2019-spring/Assignment-02.ipynb
new file mode 100644
index 0000000..d50138b
--- /dev/null
+++ b/2019-spring/Assignment-02.ipynb
@@ -0,0 +1,335 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Assignment-02, Probability Model A First Look: An Introduction of Language Model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Assignment\n",
+    "\n",
+    "1. Review the course online programming code; \n",
+    "2. Review the main questions; \n",
+    "3. Using wikipedia corpus to build a language model. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1. Review the course online programming code. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "*In this part, you should re-code the programming task in our online course.*\n",
+    "\n",
+    "> \n",
+    "> \n",
+    "\n",
+    "> \n",
+    "> \n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Review the main points of this lesson. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### 1. How to Github and Why do we use Jupyter and Pycharm; "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans: {*Put your answer here*}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### 2. What's the Probability Model?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### 3. Can you came up with some sceneraies at which we could use Probability Model?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### 4. Why do we use probability and what's the difficult points for programming based on parsing and pattern match? \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### 5. What's the Language Model;"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans: "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#####  6. Can you came up with some sceneraies at which we could use Language Model?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### 7. What's the 1-gram language model;"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### 8. What's the disadvantages and advantages of 1-gram language model;"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### 9.  What't the 2-gram models; "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### 10. what's the web crawler, and can you implement a simple crawler? "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### 11.  There may be some issues to make our crwaler programming difficult, what are these, and how do we solve them?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### 12. What't the Regular Expression and how to use?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3. Using Wikipedia dataset to finish the language model. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Step 1: You need to download the corpus from wikipedis:\n",
+    "> https://dumps.wikimedia.org/zhwiki/20190401/\n",
+    "\n",
+    "Step 2: You may need the help of wiki-extractor:\n",
+    "\n",
+    "> https://github.com/attardi/wikiextractor\n",
+    "\n",
+    "Step 3: Using the technologies and methods to finish the language model; \n",
+    "> \n",
+    "\n",
+    "Step 4: Try some interested sentence pairs, and check if your model could fit them\n",
+    "\n",
+    "> \n",
+    "\n",
+    "Step 5: If we need to solve following problems, how can language model help us? \n",
+    "\n",
+    "+ Voice Recognization.\n",
+    "+ Sogou *pinyin* input.\n",
+    "+ Auto correction in search engine. \n",
+    "+ Abnormal Detection."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Compared to the previous learned parsing and pattern match problems. What's the advantage and disavantage of Probability Based Methods? "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans: "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## (Optional)  How to solve *OOV* problem?\n",
+    "\n",
+    "If some words are not in our dictionary or corpus. When we using language model, we need to overcome this `out-of-vocabulary`(OOV) problems. There are so many intelligent man to solve this probelm. \n",
+    "\n",
+    "-- \n",
+    "\n",
+    "The first question is: \n",
+    "\n",
+    "**Q1: How did you solve this problem in your programming task?**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ans: "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then, the sencond question is: "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Q2: Read about the 'Turing-Good Estimator', can explain the main points about this method, and may implement this method in your programming task**\n",
+    "\n",
+    "Reference: \n",
+    "+ https://www.wikiwand.com/en/Good%E2%80%93Turing_frequency_estimation\n",
+    "+ https://github.com/Computing-Intelligence/References/blob/master/NLP/Natural-Language-Processing.pdf, Page-46"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "> coding in here"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}