manishanker

**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

manishanker

Use neural networks to build a model which can classify the clothing item with high accuracy:

data can be downloaded here :

Train images : http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz
Train Labels : http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz


Test Images : http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz
Test Labels: http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz

manishanker

Dataset url : 

https://raw.githubusercontent.com/manishanker/stats_ml_jun2020/master/datasets_737503_1278636_heart.csv


Attribute Information
1) age
2) sex
3) chest pain type (4 values)
4) resting blood pressure

manishanker

Dataset url : 

https://raw.githubusercontent.com/manishanker/stats_ml_jun2020/master/datasets_737503_1278636_heart.csv


Attribute Information
1) age
2) sex
3) chest pain type (4 values)
4) resting blood pressure

manishanker

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  // Get the request and its headers
  const request = event.Records[0].cf.request;
  const headers = request.headers;

  // Specify the username and password to be used
  const user = ; //add username here
  const pw = ; //add password here

manishanker

manishanker