Corso Completo su Data Analytics e Big Data Computing

3.500,00

Descrizione

Giorno 1:
Statistica
ML e Python
  • Why use a programming language
  • Python resources
  • Python Libraries for Machine learning
  • Notebook
Python e Data Analytics
  • Data Analysis
  • Manipulating, processing, cleaning, and crunching data
  • Data manipulation, calculation and graphical display
Giorno 2:
Regression and numerical prediction
  • Least squares estimation
  • Variables selection techniques
  • Nonlinearities and generalized least squares
  • Polynomial regression
  • Regression splines
  • Regression trees
  • Examples in Python
Time series Forecasting
  • Seasonal adjustment
  • Moving average
  • Exponential smoothing
  • Extrapolation
  • Linear prediction
  • Trend estimation
Time Series Database
  • InfluxDB as Time as series Database
Giorno 3:
Machine Learning Algorithms
Classification
  • Bayesian refresher
  • Naive Bayes
  • Logistic regression
  • K-Nearest neighbors
  • Exercises
Unsupervised Learning
  • K-means clustering
  • Examples
Giorno 4:
Apache Spark for Big Data Computing
  • RDD
  • Transformations 
  • Join
  • Caching
  • Dataframes and SparkSQL
  • Streaming
Practical exercises using Databricks or AWS EMR
Giorno 5:
TensorFlow e Deep Learning