Skip to main content

Featured Post

Top 10 Advance Java Interview questions?

Top 10 Advance Java Interview questions?   What are the differences between abstract classes and interfaces in Java? What is the difference between ArrayList and LinkedList in Java? What is the purpose of the finalize() method in Java? What is polymorphism in Java and how is it achieved? What are the different types of inner classes in Java? What is the difference between static and non-static methods in Java? What are the different types of exceptions in Java and how do they differ? What is the difference between checked and unchecked exceptions in Java? How does Java handle multithreading and synchronization? What are the different types of JDBC drivers in Java and how do they differ?

Best Python libraries for Machine Learning

 

Best Python libraries for Machine Learning

Machine Learning, as the name suggests, is the science of programming a computer by which they are able to learn from different kinds of data. A more general definition given by Arthur Samuel is – “Machine Learning is the field of study that gives computers the ability to learn without being explicitly programmed.” They are typically used to solve various types of life problems. 
In the older days, people used to perform Machine Learning tasks by manually coding all the algorithms and mathematical and statistical formulas. This made the processing time-consuming, tedious, and inefficient. But in the modern days, it is become very much easy and efficient compared to the olden days by various Python libraries, frameworks, and modules. Today, Python is one of the most popular programming languages for this task and it has replaced many languages in the industry, one of the reasons is its vast collection of libraries. Python libraries that used in Machine Learning are: 
 

  • Numpy
  • Scipy
  • Scikit-learn
  • Theano
  • TensorFlow
  • Keras
  • PyTorch
  • Pandas
  • Matplotlib

Comments

Popular posts from this blog

body-fitness Important of life | Comingfly

body-fitness Important of life In general, a strong candidate for the "best" title will be any easy-to-learn exercise that targets multiple muscle groups and gives you the practical strength and muscle tone to meet your fitness goals. Exercises that don't require fancy, expensive equipment earn extra credit. Here are seven of the best exercises for athletes and fitness junkies looking for a simple and effective full-body workout.

WHAT ARE NEURAL NETWORKS? | Comingfly

WHAT ARE NEURAL NETWORKS ? Neural Networks the process of machine learning are neural networks. These are brain-inspired networks of interconnected layers of algorithms, called neurons, that feed data into each other, and which can be trained to carry out specific tasks by modifying the importance attributed to input data as it passes between the layers. During training of these neural networks, the weights attached to different inputs will continue to be varied until the output from the neural network is very close to what is desired, at which point the network will have 'learned' how to carry out a particular task. A subset of machine learning is deep learning, where neural networks are expanded into sprawling networks with a huge number of layers that are trained using massive amounts of data. It is these deep neural networks that have fueled the current leap forward in the ability of computers to carry out task like speech recognition and computer vision. T here are vario...

What is PageRank (PR) ? | Comingfly

What is PageRank (PR) ? PageRank ( PR) is an algorithm used by Google Search to rank websites in their search engine results. PageRank was named after Larry Page, one of the founders of Google. PageRank is a way of measuring the importance of website pages. According to Google: It is not the only algorithm used by Google to order search engine results, but it is the first algorithm that was used by the company, and it is the best-known. Algorithm The PageRank algorithm outputs a probability distribution used to represent the likelihood that a person randomly clicking on links will arrive at any particular page. PageRank can be calculated for collections of documents of any size. It is assumed in several research papers that the distribution is evenly divided among all documents in the collection at the beginning of the computational process. The PageRank computations require several passes, called “iterations”, through the collection to adjust approximate PageRank values to more close...