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4Achievers Data Mining With Python course in Delhi will cover topics such as data pre-processing, data exploration, data visualization, predictive analytics, and more. You will also learn how to use Python libraries such as NumPy, SciPy, and Pandas to manipulate and analyze data. Additionally, you will learn how to use machine learning algorithms such as linear and logistic regression, decision trees, and neural networks to build predictive models.
Data Mining With Python is a comprehensive course offered by 4achievers, a leading training institute in Delhi. 4Achievers course is designed to help students gain a comprehensive understanding of the fundamentals of data mining and its application in the real world. 4Achievers course covers topics such as data pre-processing, data exploration, data visualization, predictive analytics, and machine learning.
4Achievers course is designed to provide students with a comprehensive learning experience. Students will be exposed to a variety of hands-on activities and projects that will help them gain a better understanding of the concepts and techniques of data mining. Students will be required to complete a series of assignments and quizzes to demonstrate their understanding of the topics covered in the course. Upon successful completion of the course, students will be awarded a global course certificate and placement assistance.
4Achievers course includes a variety of books and resources to help students gain a better understanding of the concepts and techniques of data mining. Some of the books recommended for the Data Mining With Python course include "Data Mining: Concepts and Techniques" by Jiawei Han, "Data Mining: Practical Machine Learning Tools and Techniques" by Ian H. Witten, "Data Mining: 4Achievers Textbook" by Charu C. Aggarwal, and "Data Mining for Business Analytics: Concepts, Techniques, and Applications" by Galit Shmueli.
4Achievers course also includes a variety of practical exercises and projects to help students gain a better understanding of the concepts and techniques of data mining. 4Achieversse exercises will help students gain a better understanding of the techniques and tools used in data mining. Additionally, students will be provided with a comprehensive set of resources to help them gain a better understanding of the concepts and techniques of data mining.
At the end of the course, students will be required to complete a final project to demonstrate their understanding of the concepts and techniques of data mining. Upon successful completion of the course, students will be awarded a global course certificate and placement assistance.
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Feature engineering is the process of transforming raw data into meaningful features that can help improve the accuracy of data mining models. 4Achievers involves selecting relevant and significant features from the data that can be used to build more accurate predictive models. 4Achievers also includes creating new features by combining existing features, or extracting important information from the data. Feature engineering requires understanding both the data and the task at hand, and is an important part of the data mining process.
Decision tree algorithms can be used for regression tasks by creating a tree structure with nodes that represent features of the data set and leaf nodes that represent the predicted output. 4Achievers algorithm then finds the optimal split points that lead to the greatest decrease in the variance of the output labels. This process is repeated through multiple layers of the tree until a satisfactory result is obtained.
There are a variety of evaluation metrics for machine learning models. Common ones include accuracy, precision, recall, F-measure, ROC curves, and AUC. Accuracy is a measure of how well a model can predict the correct output for a given input. Precision measures how many of the model’s positive predictions were correct. Recall measures how many of the correct outputs the model was able to identify. F-measure combines precision and recall into a single metric. ROC curves show the tradeoff between true positive rate and false positive rate. AUC is the area under the curve of the ROC curve, which is used to compare the power of different models. Other metrics used to evaluate machine learning models include log loss, mean squared error, root mean squared error, and Matthews correlation coefficient.
4Achievers Apriori algorithm is a data mining technique used to identify frequent item sets in large datasets. 4Achievers works by identifying the most frequent combinations of items in a dataset, and then using the results to create rules that can be used to predict which items are likely to be purchased together. To use the Apriori algorithm, the dataset must first be formatted into a list of transactions, with each row representing a single transaction. 4Achievers algorithm then scans the dataset to determine the most frequent sets of items that are purchased together. After this, the algorithm can then be used to generate rules that can be used to predict which items are likely to be purchased together in future transactions.
Shallow learning algorithms are simpler and tend to focus on a single task at a time. They can be used for basic classification and regression tasks, such as recognizing objects in images. On the other hand, deep learning algorithms are more complex and can be used for more complex tasks. Deep learning algorithms use multiple layers of neurons to represent data in more abstract and sophisticated ways. 4Achievers more layers you add, the deeper the network and the better it can understand complex data. Deep learning algorithms are used for tasks like natural language processing, image recognition, and autonomous driving.
4Achievers K-Nearest Neighbor algorithm is a method of making predictions by finding the k-closest data points to the query point. This algorithm works by calculating the distance between the query point and the data points, and then selecting the k-closest points. 4Achievers prediction is then determined by taking the mean of the values of the closest data points. This algorithm is useful for predicting values for data points that have similar characteristics to the query point.
Support Vector Machines (SVMs) can be used to perform regression tasks. 4Achievers is a supervised machine learning algorithm that uses support vectors which are data points that are used to create a boundary between different classes. SVMs are particularly useful when dealing with non-linear data, as they can be used to define non-linear boundaries. SVMs can also help to reduce overfitting, as they tend to introduce a minor amount of bias, which helps to avoid overfitting. SVMs can be used to fit a linear regression line, or a polynomial regression surface, to the data, depending on the complexity of the problem. SVMs are an effective tool for regression tasks and can help to better fit the data, making prediction more accurate.
Ensemble learning is a type of data mining technique that combines multiple machine learning models to generate better predictive performance than could be achieved by any of the individual models alone. 4Achievers is an effective way to reduce the variance of a model, resulting in improved accuracy and robustness in the predictions. 4Achievers can also help to reduce overfitting, which is when a model performs well on the training data but fails to generalize to unseen data.
Bayesian networks are a type of predictive model that can be used to make predictions based on data. They use probability theory to provide a graph-based representation of the relationship between variables and their potential outcomes. To make a prediction, a Bayesian network uses prior knowledge and data to calculate the probability of a specific outcome. This allows for quick and accurate predictions, as the network takes into account all of the variables and their relationships.
Text mining can be used to extract useful information from unstructured text data by automatically analyzing the text to identify patterns and relationships. This is done by using natural language processing (NLP) algorithms to extract meaning from the text. These algorithms look for keywords and phrases, as well as the context of the text, to identify and categorize the data. This extracted information can then be used to create meaningful insights and generate valuable reports. For example, text mining could be used to analyze customer feedback and determine customer satisfaction, or to analyze news articles to track trends in a particular industry. Text mining can also be used to identify relationships between entities in a text, such as the people, places, and topics mentioned in a document.
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4Achievers provides extensive post-training job assistance to the participants of Data Mining With Python Training and Certification Program. 4Achievers assist the participants in their job search and provide them with the relevant resources to help them land their desired job. 4Achievers keep in touch with the participants throughout the job search process and make sure they have the necessary skills and resources required to get their desired job. 4Achievers make sure to provide the participants with the best job opportunities available in the market and provide them with detailed information about the job openings. 4Achievers also provide career guidance and mentor the participants to help them build their professional career in the field of data mining. 4Achievers also provide them with networking opportunities and introduce them to the right people to help them further their career. 4Achievers also help the participants in preparing their resumes and provide them with interview tips.
4Achievers Data Mining With Python Training and Certification Program at 4Achievers is an in-depth and comprehensive program designed to provide students with an in-depth knowledge of data mining with Python. This program covers a wide range of topics including data extraction, data pre-processing, data analysis, data visualization, and machine learning using Python. This program is handled by experienced and certified professionals who have extensive knowledge in the areas of data mining and Python programming. 4Achievers program is divided into modules, each of which covers a specific topic related to data mining with Python. Each module is supported by a series of lectures, practical assignments, and exercises. Students can use this program to gain a better understanding of both data mining and Python programming. After successful completion of the program, students will be awarded a certification recognizing their knowledge and skills in the field of data mining with Python.
4Achievers Data Mining With Python Training and Certification Program at 4Achievers is structured in a way that provides an in-depth knowledge of the various aspects of data mining, such as predictive analytics, machine learning, data analysis, data visualization and more. 4Achievers program focuses on the use of various tools and techniques in the Python programming language to extract meaningful insights from data. 4Achievers includes both theoretical concepts and practical assignments to help participants understand the concepts better. 4Achievers course is divided into modules, each covering a specific topic related to data mining. 4Achievers modules are supplemented by quizzes, programming assignments and case studies to ensure that participants gain a comprehensive understanding of the subject.
At 4Achievers, we offer a variety of payment options for our Data Mining With Python Training and Certification Program. 4Achievers payment methods include debit/credit card, net banking, UPI, wallets, and bank transfer. 4Achievers also accept payments through Cheque, Demand Draft, and Cash. All the payments must be made in Indian Rupees. If you have any questions about payment options, please contact our customer service team for assistance.
4Achievers Data Mining with Python Training and Certification Program at 4Achievers provides a comprehensive introduction to the various tools and techniques used for data mining. 4Achievers program covers topics such as data wrangling, data exploration, data visualization, association mining, cluster analysis, sentiment analysis, predictive analytics, and deploying data mining models. 4Achievers also covers Python libraries such as Pandas, Numpy, Scikit-learn, and Seaborn. Additionally, the program provides practical hands-on experience with real-world projects and industry use cases. 4Achievers also includes access to a learning management system that allows learners to track their progress, read course material, and interact with other learners and instructors. 4Achievers program also provides support from a dedicated team of experts to ensure learners are able to get the most out of the training.
At 4Achievers, the feedback procedure for the Data Mining With Python Training and Certification Program is designed to ensure that our participants get the most out of their learning experience. 4Achievers take feedback from participants on various aspects of their learning journey, such as the quality of the course material, the interactivity of the workshops, the expertise of the trainers, the overall learning experience and more. 4Achievers feedback procedure includes a survey that is sent out to our participants post-training, where they can rate the different aspects of the program. Additionally, a dedicated support team is available to answer any questions or queries that our participants may have. 4Achievers also have a forum where participants can share their experience and learn from each other. All this is done with the aim of providing our participants with the best learning experience and ensuring they get the most out of the Data Mining With Python Training and Certification Program.
4Achievers Data Mining With Python Training and Certification Program offered by 4Achievers has a duration of 40 hours. 4Achievers is an online program that provides comprehensive knowledge and understanding of the Python programming language and its application in data mining and machine learning. 4Achievers program consists of the following modules: Introduction to Python, Data Mining with Python, Machine Learning with Python, and Python Project. 4Achievers also includes video lectures, hands-on coding exercises, quizzes, and final project. 4Achievers is designed to help participants gain the skills and knowledge necessary to become proficient in data mining and machine learning. 4Achievers program is suitable for both beginners and experienced professionals. Upon successful completion of the program, participants will earn a certificate of completion.
4Achievers assignments and exams of the Data Mining With Python Training and Certification Program at 4Achievers are designed to help students gain a comprehensive understanding of the principles of data mining and their application using the Python programming language. 4Achievers assignments range from small coding tasks to larger projects, and the exams consist of multiple-choice questions and practical tests. 4Achievers program also includes lectures and tutorials to ensure that students gain a strong knowledge base of the subject. With this comprehensive and challenging program, students can be assured that they will have the skills and knowledge necessary to succeed in the field of data mining.
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4Achievers Data Mining With Python Training and Certification Program at 4Achievers provides a comprehensive certification that validates the skills and knowledge of participants. This certification is based on the successful completion of the program's coursework, assignments, and project. A certificate of completion is issued to those who complete the program, demonstrating that the participant has the necessary knowledge and skills to use Python for data mining and analysis. 4Achievers certificate is a valuable asset that can be used to demonstrate mastery of the subject to potential employers and colleagues. 4Achievers certification also serves as a source of personal pride and accomplishment.
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First touchpoint for customer Initial handling of all customer tickets Track to closure of customer tickets by assisting the responsible teams System software and AWS/Azure infrastructure L1/L2 support Newgen solution / application L1/L2 support Responsib
Developing and deploying new applications on the windows azure PAAS platform using C#, .net core . Participation in the creation and management of databases like SQL server and MySQL Understanding of data storage technology (RDBMS, NO SQL). Manage applica
Experience of Dev Ops technologies, architectures and processes for 3 yrs Cloud Infrastructures Solutions: AWS EC2 ECS, S3 Cloudfront, RDS, Spot Instances, VPC, IAM, Security Groups, ELB etc), GCP, CI/CD Jenkins Containerization: Docker, Kubernetes System
Must have good knowledge of Google Cloud (GCP), Good To Have- AWS and. Azure Cloud automation, with overall cloud computing experience. Good knowledge of Windows Server and IIS (Internet Information Services). Good knowledge of .NET applications (ASP.Net,
Good Knowledge in both Manual Testing and Automation Testing,Strong experience in writing test scenarios and test cases Strong knowledge on Selenium, Appium, Microsoft SQL and Jmeter Adept in functional testing and reporting defects
Design, execute and report software tests, Review business / software requirements and provide inputs. Prepare test cases, test scripts and test data., Execute tests (manual / automated). Report defects and assist in their understanding., Analyse test re
Good Knowledge in both Manual Testing and Automation Testing,Strong experience in writing test scenarios and test cases Strong knowledge on Selenium, Appium, Microsoft SQL and Jmeter Adept in functional testing and reporting defects