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6 Skills Required for Machine Learning and Artificial Intelligence

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6 Skills Required for Machine Learning and Artificial Intelligence

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  1. 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.

  2. 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. That’s 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.

  3. 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 Probability 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.

  4. 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 Probability 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.

  5. 3. Data Engineering Skills For building a machine learning model, you need data for training and testing. That’s 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. That’s 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.

  6. 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 Unsupervised Learning Algorithms K-Means Clustering Also Read: What Is The Future Of Machine Learning With Python

  7. 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. scikit learn. PyTorch. Keras. DL4J. Caffe. Microsoft Cognitive Toolkit.

  8. 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. That’s 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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