Udemy

Complete DataScience with Python and Tensorflow

立即報名
  • 348 名學生
  • 更新於 7/2018
3.7
(61 個評分)
  • 提示:
  • 透過本站連結購買Udemy課程,本站將獲得推廣佣金,有助未來提供更多實用進修課程資訊給讀者。

課程資料

報名日期*
全年招生
課程級別
學習模式
修業期
11 小時 3 分鐘
教學語言
英語
授課導師
Full Stack Datascientist
評分
3.7
(61 個評分)
*提示: 以上時間表僅供參考,以機構網站為準。

課程簡介

Complete DataScience with Python and Tensorflow

Learn about machine learning, deep learning, text analytics using python and tensorflow

This course is for anyone who is interested in machine learning, deep learning and text analytics. This course assumes no previous knowledge, this course will also cover the basics of python and all the essential libraries(Pandas, Numpy, Matplotlib, Sklearn, TensorFlow, NLTK etc.) that will help students in their data science journey.

課程章節

  • 7 個章節
  • 147 堂課
  • 第 1 章 Introduction
  • 第 2 章 Python Basics
  • 第 3 章 PandasNumpyMatplotlibEDA
  • 第 4 章 Basics of Machine Learning
  • 第 5 章 Machine Learning Algorithms
  • 第 6 章 Text Analytics
  • 第 7 章 Deep Learning

課程內容

  • Learn about the basics of python as a language: basic syntax, data structure in python ,conditional statements and loops , expression and operators, Functions, Learn about essential Python libraries for data science/ analysis e.g. Pandas, Matplotlib, Numpy, Learn to do exploratory data analysis in Python, Learn how to deal with categorical variables, numerical variables, Learn about missing value analysis, outlier analysis, feature transformation etc., Learn about basics of machine learning : supervised/ unsupervised, regression/ classification, metrics used for regression and classification, Learn about popular machine learning algorithms (Keep an eye on this section, this will be updated as per demand), Learn how decision tree, association rule, naive bayes etc. works by building them from scratch in excel (don't worry if you are not familiar with excel, everything will be explained), Learn how to handle text data. Learn about NLTK : Tokenization, Lemmatization etc. Learn about regex. Learn about bag of words and TF-IDF approach. Build a text classification Model, Learn about the basics of TensorFlow, Learn about Artifical Neural Network, Convolutional Neural Network and Recurrent Neural Network and implement it on MNIST data set


評價

  • S
    Sarthak Pradhan
    4.5

    till now the content and lecture is fabulus.

  • S
    Sobhan Banerjee
    2.5

    sound quality not good

  • R
    Ravipudi Devasree
    4.0

    yes it is matching but i use anacomda for this jupter notebook

  • M
    Masoom Ali
    2.5

    python installation link is not available and behalf of that another link has not been provided. didn't explain why this library is imported and how it will work .

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