Updated Readme with links of Pandas and Numpy notebooks

Author: tirthajyoti

README.md

@@ -18,15 +18,22 @@
 * **Seaborn (`$ pip install seaborn`)**
 * **Sympy (`$ pip install sympy`)**
 ---
+
 You can start with this article that I wrote in Heartbeat magazine (on Medium platform): 
 ### ["Some Essential Hacks and Tricks for Machine Learning with Python"](https://heartbeat.fritz.ai/some-essential-hacks-and-tricks-for-machine-learning-with-python-5478bc6593f2)
 <img src="https://cookieegroup.com/wp-content/uploads/2018/10/2-1.png" width="450" height="300"/>
 
 ## Essential tutorial-type notebooks on Pandas and Numpy
 Jupyter notebooks covering a wide range of functions and operations on the topics of NumPy, Pandans, Seaborn, matplotlib etc.
-* **[Basics of Numpy array](https://github.com/tirthajyoti/PythonMachineLearning/blob/master/Pandas%20and%20Numpy/Basics%20of%20Numpy%20arrays.ipynb)**
-* **[Basics of Pandas DataFrame](https://github.com/tirthajyoti/PythonMachineLearning/blob/master/Pandas%20and%20Numpy/Basics%20of%20Pandas%20DataFrame.ipynb)**
-* **[Basics of Matplotlib and Descriptive Statistics](https://github.com/tirthajyoti/PythonMachineLearning/blob/master/Pandas%20and%20Numpy/Basics%20of%20Matplotlib%20and%20Descriptive%20Statistics.ipynb)**
+
+### [Basic Numpy operations](https://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Basics%20of%20Numpy%20arrays.ipynb)
+### [Basic Pandas operations](https://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Basics%20of%20Pandas%20DataFrame.ipynb)
+### [Basics of visualization with Matplotlib and descriptive stats](https://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Basics%20of%20Matplotlib%20and%20Descriptive%20Statistics.ipynb)
+### [Advanced Pandas operations](https://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Advanced%20Pandas%20Operations.ipynb)
+### [How to read various data sources](https://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Read_data_various_sources/How%20to%20read%20various%20sources%20in%20a%20DataFrame.ipynb)
+### [PDF reading and table processing demo](https://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Read_data_various_sources/PDF%20table%20reading%20and%20processing%20demo.ipynb)
+### [How fast are Numpy operations compared to pure Python code?](https://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/How%20fast%20are%20NumPy%20ops.ipynb) (Read my [article](https://towardsdatascience.com/why-you-should-forget-for-loop-for-data-science-code-and-embrace-vectorization-696632622d5f) on Medium related to this topic)
+### [Fast reading from Numpy using .npy file format](https://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Numpy_Reading.ipynb) (Read my [article](https://towardsdatascience.com/why-you-should-start-using-npy-file-more-often-df2a13cc0161) on Medium on this topic)
 
 ## Tutorial-type notebooks covering regression, classification, clustering, dimensionality reduction, and some basic neural network algorithms