Important Packages in Python for ML



  1. Numpy
  2. Pandas
  3. Matplotlib
  4. Seaborn
  5. Scikitlearn

Some Important datatypes for ML

  1. List
  2. Dictionary
  3. Tuple


Comments

Post a Comment

Popular posts from this blog

Classification Algorthms

Image
The purpose of this research is to put together the 7 most common types of classification algorithms along with the python code: Logistic Regression, Naïve Bayes, Stochastic Gradient Descent, K-Nearest Neighbours, Decision Tree, Random Forest, and Support Vector Machine 1 Introduction 1.1 Structured Data Classification Classification can be performed on structured or unstructured data. Classification is a technique where we categorize data into a given number of classes. The main goal of a classification problem is to identify the category/class to which a new data will fall under. Few of the terminologies encountered in machine learning – classification: Classifier: An algorithm that maps the input data to a specific category. Classification model: A classification model tries to draw some conclusion from the input values given for training. It will predict the class labels/categories for the new data. Feature: A feature is an individual measurable property of...
Read more

Julia Data Structures

Image
Julia Data Structures The following are some of the most common data structures we end up using when performing data analysis on Julia: Vector(Array)  – A vector is a 1-Dimensional array. A vector can be created by simply writing numbers separated by a comma in square brackets. If you add a semicolon, it will change the row. Vectors are widely used in linear algebra. Note that in Julia the indexing starts from 1, so if you want to access the first element of an array you’ll do A[1]. Matrix  – Another data structure that is widely used in linear algebra, it can be thought of as a multidimensional array. Here are some basic operations that can be performed in a matrix Dictionary  – Dictionary is an unordered set of  key: value  pairs, with the requirement that the keys are unique (within one dictionary). You can create a dictionary using the Dict() function. Notice that “=>” operator is used to link key with their respective values. You a...
Read more

Advantages of Python over Julia

Advantages of Python over Julia Python is a general-purpose computing language that's simple to learn, and which has become a leading language for scientific computing. Some of the reasons might still make python the best choice for data science work:  Still in the  infant  stage.  Julia is still in the development stage with its current version running on v1.1.0. It is going to get more features added in the future as the developers are continuously trying to improve its performance. More third-party packages.  The broad usage of python’s culture of custom packages remains the biggest interests of the language. Julia’s relative newness resembles the culture of software surrounding is still small. Python’s advantage of a  large  community.  A language is nowhere without the support of an active and large community around it. The community of Julia is enthusiastic and gradually growing but is still small size of the python commu...
Read more