Teachine portfolio

gistfile1.txt

**More on my Teaching portfolio:**

- E-Learning Bootcamp course structure : https://drive.google.com/file/d/1QMbaMyB1O8BAusq6ZcHoZi60fYz_8wm5/view?usp=sharing
- Module 1  Introduction to Python : *pandas, numpy, matplotlib, scikit-learn, scipy, jupyter notebook, Google colab*
 - Module 2 Introduction to Statistics : *Introduction to Probability, Conditional Probability, Bayes Theorem, Matrices, Vectors, Tensors, Measure of central tendency, Boxplot, Pearson Correlation, Chi-squared test, Z-distribution, T-test, Anova, Hypothesis Testing, Scatter Plots, Heatmaps, Multivariate analysis*
- Module 3 In troduction to ML: *PCA, Linear Regression, Logistic Regression, Decision Tree, Random Forest, SVM, Neural Network, Classification Metrics, Clustering, NLP, Time series analysis*
- Module 4 Capstone Project: *Twitter hate speech classification, Credit card fraud detection, Customer churn detection, Amazon customer reviews classification*
- Module 5 Classroom assignment : *End of module assignment on Statistics, End of module assignment on ML*
- Module 6 : *Resume building, Mock interviews, Career guidance*

Google drive link for classroom slides : https://drive.google.com/drive/folders/1toJ0Gyputqv31lJU_sXEfDPqtumCDeMD?usp=sharing

Github for classroom code examples : https://github.com/manishanker/statistics_ML_jan_2020

**Previous Bootcamps classroom recordings:**
 - Nov 2018 : https://www.youtube.com/playlist?list=PLreKEUq80ZVDlU_RJtOMGpwOkenwlycz7
- Sep 2019 : https://www.youtube.com/playlist?list=PLreKEUq80ZVB-i27N_DA-4zIB6szQSRIY
- Jan 2020 : https://www.youtube.com/playlist?list=PLreKEUq80ZVB-i27N_DA-4zIB6szQSRIY