6 Skills Required for Machine Learning And Artificial Intelligence

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6 Skills Required for Machine Learning And
Artificial Intelligence
So, You are Planning to become a Machine Learning
Engineer?. First of all, Congratulations!. You
have chosen a profitable, secure, and most
demanding career. But if you want to know the
skills required for machine learning and
artificial intelligence. ML is the same as a
Newborn child. The newborn child learns from the
instructions given by his parent and by his
self-experience. He tries to walk but he falls
down.
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1. Programming Language
Knowledge of Programming language is compulsory
for machine learning. For Machine Learning, the
most popular programming languages are Python, R,
Java, and C. As a beginner, you can start with
Python, but sometimes Python is not enough for
machine learning tasks. Thats why you should
have knowledge of all these programming
languages. But Python and R are the most wanted
languages for machine learning engineers. R
Programming language is good for statistical
operations whereas to implement mappers and
reducers in Hadoop, you should be familiar with
Java. Along with that, You should have a good
understanding of Classes, Data Structure,
algorithms, and memory management.
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2. Mathematics Skill
Knowledge of Mathematics is very important in
order to understand how machine learning and its
algorithms work. In math, the most important
topics are- Probability and Statistics Linear
Algebra a). Probability and Statistics Probabilit
y and statistics are used in- Bayes Theorem,
Probability Distribution, Sampling, and
Hypothesis Testing. b). Linear Algebra Linear
Algebra has two important terms- Matrices and
Vectors. They both used widely in Machine
Learning. Matrices are used in Image Recognition.
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2. Mathematics Skill
Knowledge of Mathematics is very important in
order to understand how machine learning and its
algorithms work. In math, the most important
topics are- Probability and Statistics Linear
Algebra a). Probability and Statistics Probabilit
y and statistics are used in- Bayes Theorem,
Probability Distribution, Sampling, and
Hypothesis Testing. b). Linear Algebra Linear
Algebra has two important terms- Matrices and
Vectors. They both used widely in Machine
Learning. Matrices are used in Image Recognition.
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3. Data Engineering Skills
For building a machine learning model, you need
data for training and testing. Thats why
knowledge of data engineering is important. Data
Science Engineering contains 3 basic steps- Data
pre-processing- Data pre-processing step is
performed before you process the data. Data
pre-processing steps are cleaning, parsing,
correcting, and consolidating the data. ETL
(Extract, Transform, and Load)- In this step, you
need to perform extraction of data from the
internet or local server, then transform the data
into a suitable format, and after that load the
data into your program. Thats why you should
have knowledge of ETL so that you can perform
these steps easily. Knowledge of Database- You
should be familiar with DBMS like SQL, Oracle
Database, and No SQL.
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4. Machine Learning Algorithms
You should have knowledge of Machine Learning
Algorithms like- Supervised Learning
Algorithms Logistic Regression. K-Nearest
Neighbors(K-NN) Support Vector Machine(SVM) Kernel
SVM. Naive Bayes Decision Tree
Classification. Random Forest Classification Unsup
ervised Learning Algorithms K-Means Clustering
Also Read What Is The Future Of Machine Learning
With Python
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5. Machine Learning Frameworks
Machine Learning Frameworks make the life of
developers and 5 Important Skills For Becoming An
Machine Learning Engineer a whole lot easier. ML
Frameworks remove the complex part of machine
learning and make it available for everyone who
wants to use it. These are some widely used
Machine Learning Frameworks- TensorFlow. Theano. s
cikit learn. PyTorch. Keras. DL4J. Caffe. Microsof
t Cognitive Toolkit.
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6. Deep Learning Algorithms
Deep learning is the subpart of machine learning.
And it is much more powerful than machine
learning. Deep learning is getting more
interesting nowadays. Thats why you should be
familiar with Deep Learning Algorithms. The most
used Deep Learning Algorithms are- Feedforward
Neural Network. Backpropagation. Convolutional
Neural Network. Recurrent Neural
Network. Generative Adversarial Networks
(GAN). So, these are 6 Skills Required for
Machine Learning and Artificial Intelligence.
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