Python AI/ML

Feature Selection

• How to select columns for machine learning?
• Bar plots: Categorical variable data quality check
• Histograms: Continuous variable data quality check

Visual Correlation Analysis

• Scatter Plots: continuous vs continuous columns
• Box Plot: continuous vs categorical columns
• Grouped Bar Charts: categorical vs categorical columns

Statistical Correlation Analysis

• Correlation value: continuous vs continuous columns
• ANOVA test: continuous vs categorical columns
• Chi-Square test: categorical vs categorical columns

Data Pre-processing before Machine Learning

• Treat missing values
• Treat Outliers in data
• Convert categorical string data to numeric

Supervised ML: Regression

• Linear Regression
• Decision Trees
• Random Forests
• Adaboost
• XGBoost
• KNN
• SVM

Supervised ML: Classification

• Logistic Regression
• Decision Tree Classifier
• Random Forest Classifier
• Adaboost Classifier
• XGBoost Classifier
• KNN Classifier
• SVM Classifier

Model Testing and validation

• Bootstrapping
• K-fold cross-validation
• Time-based sampling

Model Tuning and hyperparameter optimization

• Manual Search
• Grid Search CV
• Randomized Search CV
• Bayesian Optimization

Unsupervised ML: Clustering

• K-Means
• Hierarchical Clustering
• DBSCAN
• OPTICS

Unsupervised ML: Dimension Reduction

• Factor Analysis
• PCA
• ICA
• t-SNE
• UMAP

Association Rule Mining

• Apriori
• ECLAT
• FP-Growth

Text Analysis

• Wordcloud
• Bigram/Trigram Wordcloud
• How to extract tweets in python from the Twitter database
• Wordcloud analysis of tweets
• Sentiment Analysis of tweets

NLP

• Tokenization of text
• How to generate N-Grams
• How to do POS tagging of text
• How to do Chunking
• Named Entity Recognition(NER) using Spacy
• TF-IDF/Count Vectorization of text
• Word2Vec
• GloVe
• BERT sentiment analysis

Deep Learning

• Artificial Neural Network(Regression)
• Artificial Neural Network(Classification)
• Convolutional Neural Network(CNN)
• Long Short Term Memory Network(LSTM)