Deprecated: Return type of Ai1wm_Recursive_Directory_Iterator::hasChildren($allow_links = true) should either be compatible with RecursiveDirectoryIterator::hasChildren(bool $allowLinks = false): bool, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home1/greatsyd/public_html/staging1/wp-content/plugins/all-in-one-wp-migration-unlimited-main--old/lib/vendor/servmask/iterator/class-ai1wm-recursive-directory-iterator.php on line 57
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Deprecated: Return type of Ai1wm_Recursive_Extension_Filter::getChildren() should either be compatible with RecursiveFilterIterator::getChildren(): ?RecursiveFilterIterator, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home1/greatsyd/public_html/staging1/wp-content/plugins/all-in-one-wp-migration-unlimited-main--old/lib/vendor/servmask/filter/class-ai1wm-recursive-extension-filter.php on line 47
Deprecated: Return type of Ai1wm_Recursive_Extension_Filter::accept() should either be compatible with FilterIterator::accept(): bool, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home1/greatsyd/public_html/staging1/wp-content/plugins/all-in-one-wp-migration-unlimited-main--old/lib/vendor/servmask/filter/class-ai1wm-recursive-extension-filter.php on line 37
Deprecated: Return type of Ai1wm_Recursive_Exclude_Filter::getChildren() should either be compatible with RecursiveFilterIterator::getChildren(): ?RecursiveFilterIterator, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home1/greatsyd/public_html/staging1/wp-content/plugins/all-in-one-wp-migration-unlimited-main--old/lib/vendor/servmask/filter/class-ai1wm-recursive-exclude-filter.php on line 41
Deprecated: Return type of Ai1wm_Recursive_Exclude_Filter::accept() should either be compatible with FilterIterator::accept(): bool, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home1/greatsyd/public_html/staging1/wp-content/plugins/all-in-one-wp-migration-unlimited-main--old/lib/vendor/servmask/filter/class-ai1wm-recursive-exclude-filter.php on line 37
Deprecated: Return type of Ai1wm_Recursive_Newline_Filter::accept() should either be compatible with FilterIterator::accept(): bool, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home1/greatsyd/public_html/staging1/wp-content/plugins/all-in-one-wp-migration-unlimited-main--old/lib/vendor/servmask/filter/class-ai1wm-recursive-newline-filter.php on line 28
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{"id":27855,"date":"2023-01-02T07:23:13","date_gmt":"2023-01-02T07:23:13","guid":{"rendered":"https:\/\/greaterinsights.in\/staging1\/?page_id=27855"},"modified":"2023-11-06T06:09:36","modified_gmt":"2023-11-06T06:09:36","slug":"machine-learning-with-python","status":"publish","type":"page","link":"https:\/\/greaterinsights.in\/staging1\/machine-learning-with-python\/","title":{"rendered":"Machine Learning with Python"},"content":{"rendered":"\t\t
Machine Learning with Python<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\n\t\t\t\t\t\t
\u00a0Machine Learning with Python course focuses on giving your teams a serious head-start and practical approach on building deployable machine learning models by offering an in-depth understanding of the three major types of machine learning algorithms, comprising of supervised, unsupervised, and reinforcement learning using the most widely used programming language. Learn the various methods for implementing these algorithms with associated business use cases.<\/p>
\u00a0Help your team gain comprehensive knowledge of different Classification models and their evaluation techniques. Machine Learning training also introduces you to advanced topics of Machine Learning such as Natural Language Processing (NLP) and Artificial Neural Networks<\/p>
Work on various data pre-processing techniques, evaluating data sufficiency, different prediction and classification techniques, implementation examples, evaluation methodologies and a comprehensive view of how to go about defining and implementing your Machine Learning solution.<\/p>
\u00a0Using our advanced Cloud labs, get seamless hands-on experience working with Python\u2019s functions and libraries for Machine Learning projects. With easy to follow step-by-step instructions, you will learn to implement all Machine Learning algorithms taught in this course using the popular Python programming language.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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At the end of the training, participants will be able to:<\/h3><\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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1.\u00a0 Appreciate the breadth & depth of ML applications and use cases in real-world scenarios.<\/li>
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2. Import and wrangle data using Python libraries and divide them into training and test datasets<\/li>
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3. Data preprocessing techniques, Univariate and Multivariate analysis, Missing values and outlier treatment etc<\/li>
\u00a0<\/li>
4. Implement linear and polynomial regression, understand Ridge and lasso Regression,<\/li>
\u00a0<\/li>
5. Implement various type of classification methods including SVM, Naive bayes, decision tree, and random forest<\/li>
\u00a0<\/li>
6. Interpret Unsupervised learning and learn to use clustering algorithms<\/li>
\u00a0<\/li>
7. Tuning of ML solutions, Bias-variance tradeoff, Minibatch, and Shuffling, Overfitting avoidance<\/li>
\u00a0<\/li>
8. Basics of Neural Networks, Perceptron, MLP<\/li>
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9. Build real-world solutions using MLP<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t