Showing my daily progress in understanding machine learning.
Day 1 - Numpy : https://colab.research.google.com/drive/1grgd5MK6LwFKVrEZpjw-hXDFFzCVjWpH
Day 2 - Pandas (Part-1) : https://colab.research.google.com/drive/1mJmCEuJk6a_8tDTqTm83XPocUjCQPs98?usp=sharing
Day 3 -
-
Pandas (Part-2) : https://colab.research.google.com/drive/1PmSxZfhY8VS09nWFjsNVRLELco_W7SP5?usp=sharing
-
Matplotlib (Part-1) : https://colab.research.google.com/drive/1_FMyeBMY3X-d3Lpj63GNpQ31tpSBgM8L?usp=sharing
Day 4 -
-
Matplotlib (Part-2) : https://colab.research.google.com/drive/1XY5P2jgxPt6nx37yi5HdHgy6ckPCKlu_?usp=sharing
-
Seaborn : https://colab.research.google.com/drive/1fkCKYAGRFUe-aRWK7kp5F54gVXL0RGzV?usp=sharing
ASSESSMENT -
- NumPy : https://colab.research.google.com/drive/1KXcauiUm9oLUHazMm43tMuNnBYVHZnjT?usp=sharing
- Pandas : https://colab.research.google.com/drive/1I-f7vQaQ8EXqGuLQtM3WeIkAEwirLgaH?usp=sharing
- Matplotlib : https://colab.research.google.com/drive/1tSunJFDPcmZqH7IwWRFMeSkt87aeDA7x?usp=sharing
- Seaborn : https://colab.research.google.com/drive/18ELv1xQs9Y5pbjE4I0Mq_E10JFFqh9jS?usp=sharing
Day 5 - Statistics (Done on Notebook)
- Measures of Central Tendancy - Mean, Median, Mode
- Meausres of Variability - Range, Variance, Standard Deviation, IQR
- Graphical Representation - All Plots
- Interferential - Probability Distribution, Hypothesis Testing, Regression Analysis, Confidence Interval
Day 6 - Statistics (Done on Notebook) Continued
- Interferential - Probability Distribution - Conditional Probability, Bayes Theorem, Rules, Complementary Probability, Sample Space etc.
Day 7 - Statistics (Done on Notebook) Continued
- Interferential - Hypothesis Testing, Regression Analysis, Confidence Interval
Day 8 - Features Engineering
- Colab - https://colab.research.google.com/drive/1Nqkj84dTdImtAPtPkuLw_qmITd3w9hCy?usp=sharing
- Done on Notebook