Top 5 Best Machine Learning Frameworks in 2020.
Machine learning is a subset of AI which allows a machine to
automatically learn from past data without programming explicitly, every tech companies are shifting towards
being more “AI-enabled”, so let’s
discuss what top 5 best ML Frameworks
are in 2020….
What is Machine Learning?
Machine Learning is basically an application of Artificial Intelligence which lets the
program to “learn on their own” using statistical data collected from the user without
being explicitly programmed. Machine
learning focuses on the development of computer programs that can access
data and use it to learn for themselves. Machine
Learning has seen as a subset of Artificial
Intelligence, Machine Learning
algorithms build a mathematical model based on sample data, known as "training data", in order to make
predictions or decisions without being explicitly programmed to perform the
task.
Machine Learning Algorithms can be classified
as- Supervised and Unsupervised
·
Supervised Machine Learning- SML
Algorithms are
applied in building a mathematical model of a set of data which contains both
inputs and the desired outputs. In simple words, SML applies the data which has been learned in the past to
predict future predictions and hence giving the desired outputs. The system
is able to provide targets for any new input after sufficient training. It can also learn itself with
provided and correct the mistakes, if any.
·
Unsupervised Machine Learning-UML
Algorithms use
sets of raw data and use it for processing structure in data like grouping or
clustering of data points. The algorithms, therefore, learn from test data that
has not been labeled, classified or categorized. In simple words, Unsupervised Machine Learning are used when
the information used to train is neither classified nor labeled. UML is not fully capable to find out
the right output rather it explores the data in order to find out the pattern
and draw inferences from the unlabeled data.
Top 5 Machine Learning Platforms in 2020-
1. TensorFlow- Developed
by Google, TensorFlow is an
open-source, JavaScript library and
one of the best machine learning
frameworks of 2020. It is a free platform with APIs that help in building
and training the ML models. Developers can run the framework using CPUs and
GPUs both. TensorFlow can also
assist in Human pose automation. TensorFlow
is advantageous as it can be used in two ways, Script Tags
or by installation via NPM. However, TensorFlow
is sometimes found hard to learn and understand for beginners.
2.
Google Cloud ML Engine-Google’s
Cloud ML lets the
user explore deep learning in ML
and offer training for amateurs, among other services for building machine learning models. Data
Scientists and Developers use ML engine
to predict various fields and domains. If you are looking for deep learning and
ML model training and building, you
should try once ML Engine. Many
companies use the framework to speed up email responses to customers and
detecting clouds in a satellite image.
3. Apache Mahout- Apache Mahout is one Deep Learning platform operating on a distributed linear algebra
framework to scribe and implement ML
algorithms. Apache Mahout
helps mathematicians, statisticians, and data scientists for executing their
algorithms. Apache Mahout provides
algorithms for Pre-processors, Regression, Clustering, Recommenders, and
Distributed Linear Algebra, Additionally, Java
libraries are included for common math operations. Apache Mahout often follows a distributed linear algebra framework.
However, it is observed sometimes Apache
Mahout misses certain algorithms from its systems.
4. Shogun-Shogun is yet another open-source machine
learning framework compatible with the C++
programming language. It is a free platform that developers can use to
design algorithms and data structures, primarily for ML problems in education and research. Shogun was designed by Gunnar Raetsch and Soeren Sonnenburg in 1999
to support vector machines for classifications and regression problems, plus
large-scale learning.
5. Sci-Kit Learn-Sci-Kit is a machine learning platform that supports development in Python with a library for Python programming language. Sci-Kit Learn
also supports designing models and algorithms for classifications, regression,
clustering, pre-processing, Dimensional reduction, and Model selection. Sci-Kit is arguably one of the easiest
platforms for even amateur developers with its detailed documentation readily
available, you can even change the pre-set parameters for algorithms when in
use.
Conclusion-Machine Learning is getting bigger day by day, top
product companies are shifting towards automation in order to control operational cost and increase efficiency, what are your views on this. Also, do
let us know, according to you what some of the best Machine Learning Frameworks are in 2020 that we haven’t
accounted for.
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