data 37
- Let's try: Apache Beam part 8 - Tags & Side inputs
- Let's try: Apache Beam part 7 - custom IO
- Let's try: Apache Beam part 6 - instant IO
- Data contracts in action (Python)
- Data contracts in action (NodeJS)
- Let's try: Apache Beam part 5 - transform it with Beam functions
- Let's try: Apache Beam part 4 - live on Google Dataflow
- Let's try: Apache Beam part 3 - my own functions
- Let's try: Apache Beam part 2 - draw the graph
- Let's try: Apache Beam part 1 - simple batch
- CloudEvents standard
- DAG integrity - unit test your DAG before deploying
- Let's try: Apache Airflow 2
- Let's try: Apache Airflow
- Note of data science training EP 14 END – Data scientists did their mistakes
- Note of data science training EP 13: Regularization – make it regular with Regularization
- Do a presentation quick with Data Studio
- Note of data science training EP 12: skimage – Look out carefully
- Note of data science training EP 11: NLP & Spacy – Languages are borderless
- Note of data science training EP 10: Cluster – collecting and clustering
- Note of data science training EP 9: NetworkX – Map of Marauder in real world
- Note of data science training EP 8: Ensemble – Avenger's ensemble
- Note of data science training EP 7: Metrics – It is qualified
- Note of data science training EP 6: Decision Tree – At a point of distraction
- Note of data science training EP 5: Logistic Regression & Dummy Classifier – Divide and Predict
- Note of data science training EP 4: Scikit-learn & Linear Regression – Linear trending
- Note of data science training EP 3: Matplotlib & Seaborn – Luxury visualization
- Note of data science training EP 2: Pandas & Matplotlib – from a thousand mile above
- Note of data science training EP 1: Intro – unboxing
- Data Integration (EP 3 end) - clock-work
- Data Integration (EP 2) - Take it out
- Data Integration (EP 1) – Give me your data
- Data 4.0 (Part 5)
- Data 4.0 (Part 4)
- Data 4.0 (Part 3)
- Data 4.0 (Part 2)
- Data 4.0 (Part 1)