Data Science For Beginners: Hands-On Data Science In Python

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Beschreibung

Description

Data Science, Machine Learning and Artificial Intelligence are the most demanding skills in today's world,

Almost every Multi-National company is working on these new technologies.

With this Mega Course you will learn all the required tools for Data Science from very beginning!

We will cover below topics:

  • 1) Data Analysis with Numpy: NumPy Arrays, Indexing and Selection, NumPy Operations
  • 2) Data Analysis with Pandas: Pandas Series, DataFrames, Multi-index and index hierarchy, Working with Missing Data, Groupby Function, Merging Joining and Concatenating DataFrames, Pandas Operations, Reading and Writing Files
  • 3) Data Visualization with Matplotlib library
  • 4) Data Pre…

Gesamte Beschreibung lesen

Frequently asked questions

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Noch nicht den perfekten Kurs gefunden? Verwandte Themen: Data Science Python, Data Science, Python, Big Data und Data Analytics.

Description

Data Science, Machine Learning and Artificial Intelligence are the most demanding skills in today's world,

Almost every Multi-National company is working on these new technologies.

With this Mega Course you will learn all the required tools for Data Science from very beginning!

We will cover below topics:

  • 1) Data Analysis with Numpy: NumPy Arrays, Indexing and Selection, NumPy Operations
  • 2) Data Analysis with Pandas: Pandas Series, DataFrames, Multi-index and index hierarchy, Working with Missing Data, Groupby Function, Merging Joining and Concatenating DataFrames, Pandas Operations, Reading and Writing Files
  • 3) Data Visualization with Matplotlib library
  • 4) Data Pre-Processing: Importing Libraries, Importing Dataset, Working with missing data, Encoding categorical data, Splitting dataset into train and test set, Feature scaling
  • 5) Regression Analysis: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, Support Vector Machine, Decision Tree, Random Forest, Evaluating the Model Performance
  • 6) Classification Techniques: Logistic Regression, KNN, SVM, Naïve Bayes, Decision Tree, Random Forest
  • 7) Cluster Analysis: K means, Hierarchical
  • 8) Natural Language Processing: NLTK, Tokenization, Stemming, Lemmatization, Stop Words, POS Tagging, Chunking, Named Entity Recognition, Text Classification
  • 9) Dimensionality Reduction: Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA)

Learn Data Science to advance your Career and Increase your knowledge in a fun and practical way !

Regards,

Vijay Gadhave

Basic knowledge

  • No Prior Knowledge or Experience Needed, Only a Passion to Learn

What will you learn

  • The Complete Understanding of Machine Learning from the Scratch
  • Learn Python for Data Science and Machine Learning
  • Learn How to Pre-Process the Data
  • Perform Linear and Logistic Regressions in Python
  • Learn Different Regression Algorithms in Python
  • Learn to Apply Different Classification Algorithms in Python
  • K means and Hierarchical Cluster Analysis
  • Data Analysis with NumPy and Pandas
  • Data Visualization with Matplotlib library
  • DataFrames, Pandas Series, Pandas Matrix
  • NumPy Arrays, Indexing, Selection, Numpy Operations
  • Learn to Work with Missing Data
  • Natural Language Processing
  • Dimensionality Reduction: PCA and LDA

https://www.simplivlearning.com/dataandanalytics/data-science-for-beginners-hands-on-data-science-in-python

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