Over the last few years I have explored, programmed, worked in, researched and taught Data Science / AI / ML / Analytics / Decision Science to multiple students and with many software professionals. I have collected many keywords that you can google and explore. This will help you to keep pace and learn about things happening is these areas. It’s like a glossary of words to search over internet. It’s a mix and match of technologies, algorithms, concepts, AI / ML / Information Technology terms, BigData words and so on in no particular order. I will keep expanding this till it’s a relatively exhaustive list.

• Automatic Machine Learning
• Transfer Learning
• Explainable Machine Learning
• Keras
• PyTorch
• MLR
• R
• Python
• Ggplot2
• MathplotLib
• MLib
• Spark
• Hadoop
• Tableau
• Chatbots
• Talend
• MongoDB
• Neo4j
• Kafka
• ELK
• NoSQL
• Cassandra
• AWS SageMaker
• SVM
• Decision Trees
• Regression: Logistic, Multiple, Simple Linear, Polynomial
• Scikit Learn
• KNIME
• BERT
• NLG
• NLP
• Random Forest
• Hyper parameters
• Boosting
• Association rules / mining – Apriori, FP-Growth
• Data mining
• OpenCV
• Self driving cars
• AI / Memory embedded SOCs, GPUs, TPUs
• Neural engine chipsets
• Neural Networks
• Deep Learning
• EDA
• Statistical & Algorithmic modelling
• Sampling
• Probability distributions
• Hypothesis testing
• Intervals, extrapolation, interpolation
• Scaling
• Normalization
• Agents, search, constraint satisfaction
• Rules based systems
• Semantic net
• Propositional logic
• Fuzzy reasoning
• Probabilistic learning
• First order logic
• Game theory
• Pipeline building
• Ludwig
• Bayesian belief networks
• Anaconda Navigator
• Jupyter
• Synthetic data
• Google dataset search
• Kaggle
• CNN / RNN / Feed forward / Back propagation / Multi-layer
• Tensorflow
• Deepfakes
• KNN
• K means clustering
• Naive Bayes
• Dimensionality reduction
• Feature engineering
• Supervised, unsupervised & reinforcement learning
• Markov model
• Time series
• Categorical & Continuous data
• Imputation
• Data analysis
• Classification / Clustering / Trees / Hyperplane
• Differential calculus
• Testing & training data
• Visualization
• Missing data treatment
• Scipy
• Pandas
• LightGBM
• Numpy
• Dplyr
• Google Collaboratory
• PyCharm
• Plotly
• Shiny
• Caret
• NLTK, Stanford NLP, OpenNLP
• Artificial intelligence
• SQL / PLSQL
• Data warehousing
• Cognitive computing
• Coral
• Arduino
• Raspberry Pi
• RTOS
• DARPA Spectrum Challenge
• 100 page ML book
• Equations, Functions, and Graphs
• Differentiation and Optimization
• Vectors and Matrices
• Statistics and Probability
• Operations management & research
• Unstructured, semi-structured & structured data
• Five Vs
• Descriptive, Predictive & Prescriptive analytics
• Model accuracy
• IoT / IIoT
• Recommendation Systems
• Real Time Analytics
• Google Analytics

If you are learning something by googling these topics, feel free to provide suggestions for adding more words here. You are welcome to discuss / suggest on top of this article as well. Thank you for reading.

Email me: Neil@TechAndTrain.com

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