I got your response from urbanpro regarding Data Science Using R and Python Programming. And, I completed B.Tech with MBA also Pursuing Ph.D in the field of Data Analytics and Business Intelligence in BITS Pilani,So far more than 1500 professionals trained and many colleges across India trained the students. Kindly, Share your email ID will send you the detailed course brochure. This course is designed for professionals who want to explore data analysis using R Programming and it includes Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression and Random Forest Regression and Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification and Random Forest Classification and then Clustering: K-Means and Hierarchical Clustering and then Association Rule Learning: Apriori Algorithm and Eclat and then Reinforcement Learning and then Natural Language Processing and Deep Learning: Artificial Neural Networks, Convolutional Neural Networks and Dimensionality Reduction: PCA, LDA, Kernel PCA. Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.
I got your response from urbanpro regarding Data Science Using R and Python Programming. And, I completed B.Tech with MBA also Pursuing Ph.D in the field of Data Analytics and Business Intelligence in BITS Pilani,So far more than 1500 professionals trained and many colleges across India trained the students. Kindly, Share your email ID will send you the detailed course brochure. This course is designed for professionals who want to explore data analysis using R Programming and it includes Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression and Random Forest Regression and Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification and Random Forest Classification and then Clustering: K-Means and Hierarchical Clustering and then Association Rule Learning: Apriori Algorithm and Eclat and then Reinforcement Learning and then Natural Language Processing and Deep Learning: Artificial Neural Networks, Convolutional Neural Networks and Dimensionality Reduction: PCA, LDA, Kernel PCA. Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.
I have 2.8 year's of experience on Data Science. Experienced Data scientist (3 years) with an Extensive history of working in the field of Machine learning and Deep learning. Skilled in R, Python, Azure Microsoft, knime, orange, Data Cleaning and Strong information technology professional with a Master of Technology (M.Tech.) focused in CSE from VIT-University.
I have 2.8 year's of experience on Data Science. Experienced Data scientist (3 years) with an Extensive history of working in the field of Machine learning and Deep learning. Skilled in R, Python, Azure Microsoft, knime, orange, Data Cleaning and Strong information technology professional with a Master of Technology (M.Tech.) focused in CSE from VIT-University.
Analytixpro has educated more than 2,000 candidates for professional courses, such as Data Science, Python Programming, Digital marketing etc and trained employees of 60+ reputed organizations on Data Analytics, Digital Marketing, Data Visualization, Statistics, Soft Skills etc.
Analytixpro has educated more than 2,000 candidates for professional courses, such as Data Science, Python Programming, Digital marketing etc and trained employees of 60+ reputed organizations on Data Analytics, Digital Marketing, Data Visualization, Statistics, Soft Skills etc.
Cognizant, Associate (ML) Client: Google (DBM) Sep 2018- Present Objective: To decrease escalation count by predicting whether a ticket is going to meet SLA or not. â?¢ Built automated tool to navigate tickets to top performing Agent. â?¢ Joined tables and Cleansed data sets to form consolidated table in PLX SQL database. â?¢ Clustered Agents based on tenure,submitter location, shift timing, language of ticket â?¢ Predicted whether the ticket meet SLA or Not and increasing TFS SLA depending upon the dependency. â?¢ Used K-Means, XG-Boost and Random Forest. â?¢ Developed and modified business requirement documents in Agile Methodology . Experienced in Google SQL. â?¢ Packages: Dplyr, Lubridate, Dremel SQL, Random Forest Client: Apple Aug 2018 Objective: To improve operation metrics of operators by predicting No Action Required cases. â?¢ Built automated tool to predict whether a ticket is going to be NAR or not. â?¢ Cleansed and validated data sets based on business requirements. â?¢ Used Word2Vec and Glove Model to find the relation between the dependent and independent variables. â?¢ Used Na�¯ve Bayes to perform text classification. â?¢ Displayed trends and probability of being a ticket to be NAR or not. â?¢ Used Nltk, Word2Vec, Glove, CNN Client: Google July 2018 Objective: To find the root cause of increase or decrease in Map Accuracy score and providing insights to improve operation metrics. â?¢ Modify databases and tables based on client needs. Developed stored procedures and functions to modularize the ad hoc queries. â?¢ Cleansed and validated tables to provide insights in data to increase map accuracy â?¢ Built dashboards, debugged and explored reasons behind discrepancies in data. â?¢ Created and Documented test cases to be used for validation of data to satisfy the business requirements. â?¢ Packages: Dremel SQL, PLX dashboards Client: Google Apr 2018-June 2018 Objective: To automate, maintain ,validate and visualize metrics to understand the changes in operation metrics. â?¢ Automated existing dashboards by creating new temporary tables and stored procedures. â?¢ Conducted data preparation, and outlier detection using SQL queries and explored the key reasons. â?¢ Built dashboards with business objective as a primary focus. Conducted data preparation, and outlier detection using SQL queries and explored the KPI. â?¢ Packages: Dremel SQL, PLX dashboards INSOFE, Data Scientist Intern Client: Colombian Power Distribution Unit: Apr 2017- Mar 2018 Objective: Provide Rules to decrease Loss at a geographical location. â?¢ Clustered meters based on Geographical Location using K Means Clustering.. â?¢ Predicted technical Power loss for clustered meters using Linear Regression and Has provided decision rules to minimize technical loss at a location. â?¢ Mapped predicted loss to a map-based UI using Folium API. â?¢ Dumped data into SQL table. Used prediction column as source to display loss on webpage. â?¢ Packages: : Dplyr, Lubridate,Sqldf, kkmeans ,lm
Cognizant, Associate (ML) Client: Google (DBM) Sep 2018- Present Objective: To decrease escalation count by predicting whether a ticket is going to meet SLA or not. â?¢ Built automated tool to navigate tickets to top performing Agent. â?¢ Joined tables and Cleansed data sets to form consolidated table in PLX SQL database. â?¢ Clustered Agents based on tenure,submitter location, shift timing, language of ticket â?¢ Predicted whether the ticket meet SLA or Not and increasing TFS SLA depending upon the dependency. â?¢ Used K-Means, XG-Boost and Random Forest. â?¢ Developed and modified business requirement documents in Agile Methodology . Experienced in Google SQL. â?¢ Packages: Dplyr, Lubridate, Dremel SQL, Random Forest Client: Apple Aug 2018 Objective: To improve operation metrics of operators by predicting No Action Required cases. â?¢ Built automated tool to predict whether a ticket is going to be NAR or not. â?¢ Cleansed and validated data sets based on business requirements. â?¢ Used Word2Vec and Glove Model to find the relation between the dependent and independent variables. â?¢ Used Na�¯ve Bayes to perform text classification. â?¢ Displayed trends and probability of being a ticket to be NAR or not. â?¢ Used Nltk, Word2Vec, Glove, CNN Client: Google July 2018 Objective: To find the root cause of increase or decrease in Map Accuracy score and providing insights to improve operation metrics. â?¢ Modify databases and tables based on client needs. Developed stored procedures and functions to modularize the ad hoc queries. â?¢ Cleansed and validated tables to provide insights in data to increase map accuracy â?¢ Built dashboards, debugged and explored reasons behind discrepancies in data. â?¢ Created and Documented test cases to be used for validation of data to satisfy the business requirements. â?¢ Packages: Dremel SQL, PLX dashboards Client: Google Apr 2018-June 2018 Objective: To automate, maintain ,validate and visualize metrics to understand the changes in operation metrics. â?¢ Automated existing dashboards by creating new temporary tables and stored procedures. â?¢ Conducted data preparation, and outlier detection using SQL queries and explored the key reasons. â?¢ Built dashboards with business objective as a primary focus. Conducted data preparation, and outlier detection using SQL queries and explored the KPI. â?¢ Packages: Dremel SQL, PLX dashboards INSOFE, Data Scientist Intern Client: Colombian Power Distribution Unit: Apr 2017- Mar 2018 Objective: Provide Rules to decrease Loss at a geographical location. â?¢ Clustered meters based on Geographical Location using K Means Clustering.. â?¢ Predicted technical Power loss for clustered meters using Linear Regression and Has provided decision rules to minimize technical loss at a location. â?¢ Mapped predicted loss to a map-based UI using Folium API. â?¢ Dumped data into SQL table. Used prediction column as source to display loss on webpage. â?¢ Packages: : Dplyr, Lubridate,Sqldf, kkmeans ,lm
Am kavya from AIE INFO and I work for it .. Am a consultant ...we provide course on data science and artificial intelligence, machine learning and python
Am kavya from AIE INFO and I work for it .. Am a consultant ...we provide course on data science and artificial intelligence, machine learning and python
Having statistics background with 2 years of experience in data science. I am giving online tution to who is interested in data science, machine learning ,statistics, python and R. I have received ibm digital badges for various courses related data science and sql services.
Having statistics background with 2 years of experience in data science. I am giving online tution to who is interested in data science, machine learning ,statistics, python and R. I have received ibm digital badges for various courses related data science and sql services.
I am a Data scientist having more than 1 year of practical experience in Applied AI. I have done Post Graduation in Data science from INSOFE Hyderabad and won scholarship. My key skills are Machine Learning, Deep Learning, Natural Language Processing and Data Analytics. I am giving online classes for people from various backgrounds from past 1 year and have helped them in cracking interviews with key interview concepts and respective real world applications.
I am a Data scientist having more than 1 year of practical experience in Applied AI. I have done Post Graduation in Data science from INSOFE Hyderabad and won scholarship. My key skills are Machine Learning, Deep Learning, Natural Language Processing and Data Analytics. I am giving online classes for people from various backgrounds from past 1 year and have helped them in cracking interviews with key interview concepts and respective real world applications.
I have 8 years of experience in teaching. Data science with real time scenarios. Will supprt you for Resume preparations, will do mock interviews, will be available completely online only.
I have 8 years of experience in teaching. Data science with real time scenarios. Will supprt you for Resume preparations, will do mock interviews, will be available completely online only.
Analytics Path Provides Data Science Classes , Data Analysis Classes to all Students.
Analytics Path Provides Data Science Classes , Data Analysis Classes to all Students.
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