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Expand Up @@ -187,13 +187,95 @@ Link To the [video.](https://www.youtube.com/watch?v=BqgTU7_cBnk&list=PLQVvvaa0Q

## K Means Clustering | Day 43
Moved to Unsupervised Learning and studied about Clustering.
Working on my website check it out [avikjain.me](avikjain.me)
Working on my website check it out [avikjain.me](http://www.avikjain.me/)
Also Found A wonderful animation that can help to easily understand K - Means Clustering [Link](http://shabal.in/visuals/kmeans/6.html)

<p align="center">
<img src="https://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%2043.jpg">
</p>

## K Means Clustering Implementation | Day 44
Implemented K Means Clustering. Check the code [here.]()

## Digging Deeper | NUMPY | Day 45
Got a new book "Python Data Science HandBook" by JK VanderPlas Check the Jupyter notebooks [here.](https://github.com/jakevdp/PythonDataScienceHandbook)
<br>Started with chapter 2 : Introduction to Numpy. Covered topics like Data Types, Numpy arrays and Computations on Numpy arrays.
<br>Check the code -
<br>[Introduction to NumPy](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.00-Introduction-to-NumPy.ipynb)
<br>[Understanding Data Types in Python](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.01-Understanding-Data-Types.ipynb)
<br>[The Basics of NumPy Arrays](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.02-The-Basics-Of-NumPy-Arrays.ipynb)
<br>[Computation on NumPy Arrays: Universal Functions](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.03-Computation-on-arrays-ufuncs.ipynb)

## Digging Deeper | NUMPY | Day 46
Chapter 2 : Aggregations, Comparisions and Broadcasting
<br>Link to Notebook:
<br>[Aggregations: Min, Max, and Everything In Between](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.04-Computation-on-arrays-aggregates.ipynb)
<br>[Computation on Arrays: Broadcasting](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.05-Computation-on-arrays-broadcasting.ipynb)
<br>[Comparisons, Masks, and Boolean Logic](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.06-Boolean-Arrays-and-Masks.ipynb)

## Digging Deeper | NUMPY | Day 47
Chapter 2 : Fancy Indexing, sorting arrays, Struchered Data
<br>Link to Notebook:
<br>[Fancy Indexing](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.07-Fancy-Indexing.ipynb)
<br>[Sorting Arrays](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.08-Sorting.ipynb)
<br>[Structured Data: NumPy's Structured Arrays](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.09-<br>Structured-Data-NumPy.ipynb)

## Digging Deeper | PANDAS | Day 48
Chapter 3 : Data Manipulation with Pandas
<br> Covered Various topics like Pandas Objects, Data Indexing and Selection, Operating on Data, Handling Missing Data, Hierarchical Indexing, ConCat and Append.
<br>Link To the Notebooks:
<br>[Data Manipulation with Pandas](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.00-Introduction-to-Pandas.ipynb)
<br>[Introducing Pandas Objects](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.01-Introducing-Pandas-Objects.ipynb)
<br>[Data Indexing and Selection](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.02-Data-Indexing-and-Selection.ipynb)
<br>[Operating on Data in Pandas](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.03-Operations-in-Pandas.ipynb)
<br>[Handling Missing Data](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.04-Missing-Values.ipynb)
<br>[Hierarchical Indexing](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.05-Hierarchical-Indexing.ipynb)
<br>[Combining Datasets: Concat and Append](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.06-Concat-And-Append.ipynb)

## Digging Deeper | PANDAS | Day 49
Chapter 3: Completed following topics- Merge and Join, Aggregation and grouping and Pivot Tables.
<br>[Combining Datasets: Merge and Join](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.07-Merge-and-Join.ipynb)
<br>[Aggregation and Grouping](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.08-Aggregation-and-Grouping.ipynb)
<br>[Pivot Tables](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.09-Pivot-Tables.ipynb)

## Digging Deeper | PANDAS | Day 50
Chapter 3: Vectorized Strings Operations, Working with Time Series
<br>Links to Notebooks:
<br>[Vectorized String Operations](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.10-Working-With-Strings.ipynb)
<br>[Working with Time Series](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.11-Working-with-Time-Series.ipynb)
<br>[High-Performance Pandas: eval() and query()](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.12-Performance-Eval-and-Query.ipynb)

## Digging Deeper | MATPLOTLIB | Day 51
Chapter 4: Visualization with Matplotlib
Learned about Simple Line Plots, Simple Scatter Plotsand Density and Contour Plots.
<br>Links to Notebooks:
<br>[Visualization with Matplotlib](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.00-Introduction-To-Matplotlib.ipynb)
<br>[Simple Line Plots](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.01-Simple-Line-Plots.ipynb)
<br>[Simple Scatter Plots](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.02-Simple-Scatter-Plots.ipynb)
<br>[Visualizing Errors](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.03-Errorbars.ipynb)
<br>[Density and Contour Plots](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.04-Density-and-Contour-Plots.ipynb)

## Digging Deeper | MATPLOTLIB | Day 52
Chapter 4: Visualization with Matplotlib
Learned about Histograms, How to customize plot legends, colorbars, and buliding Multiple Subplots.
<br>Links to Notebooks:
<br>[Histograms, Binnings, and Density](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.05-Histograms-and-Binnings.ipynb)
<br>[Customizing Plot Legends](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.06-Customizing-Legends.ipynb)
<br>[Customizing Colorbars](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.07-Customizing-Colorbars.ipynb)
<br>[Multiple Subplots](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.08-Multiple-Subplots.ipynb)
<br>[Text and Annotation](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.09-Text-and-Annotation.ipynb)

## Digging Deeper | MATPLOTLIB | Day 53
Chapter 4: Covered Three Dimensional Plotting in Mathplotlib.
<br>Links to Notebooks:
<br>[Three-Dimensional Plotting in Matplotlib](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.12-Three-Dimensional-Plotting.ipynb)

## Hierarchical Clustering | Day 54
Studied about Hierarchical Clustering.
Check out this amazing [Visualization.](https://cdn-images-1.medium.com/max/800/1*ET8kCcPpr893vNZFs8j4xg.gif)
<p align="center">
<img src="https://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%2054.jpg">
</p>a

## Digging Deeper | | Day 45
## Hierarchical Clustering Implementation | Day 55

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