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Tensorflow Multivariate Multistep Tutorial on www.tensorflow.org/tutorials/structured_data/time_series

$10-30 USD

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Posted almost 4 years ago

$10-30 USD

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If You know this tutorial You know that the dataset is containing more than 300,000 rows of the data. I want to adapt the Tutorial to 200 days of data, that I have prepared in DataFrame for 17 Rows. In this part of the code: past_history = 720 future_target = 72 STEP = 6 x_train_single, y_train_single = multivariate_data(dataset, dataset[:, 1], 0, TRAIN_SPLIT, past_history, future_target, STEP, single_step=True) x_val_single, y_val_single = multivariate_data(dataset, dataset[:, 1], TRAIN_SPLIT, None, past_history, future_target, STEP, single_step=True) I am getting an Error. I think that I must change some parameters, so that only 200 days of history is considered. See the Jupyter workbook as pdf: Can You help me?
Project ID: 24718318

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Hi there! I hope you are doing well. I am professional ML developer with certification. I implemented some complex Deeplearning models. This task is basic one , pin me back if you are interested. I hope you would prefer expertise over low-ball bids.
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Note: I can help you with this. This work is really matching with my experience and I have done a lot of projects like this. Please let me talk further through chat so we will move forward and I will give you a solution as you needed. Greetings! Welcome to DEEP LEARNING, MACHINE LEARNING & ARTIFICIAL INTELLIGENCE Developer by using Python! I hope you are doing good. Well, regarding this project, I have extensive 8+ years of experience in DEEP LEARNING, MACHINE LEARNING & ARTIFICIAL INTELLIGENCE projects using Python. I will work in an efficient and correct way. Give me work, I will surely complete work within the required time. I have been working for the following field related projects: Classification Regression Clustering Dimensionality Reduction Prediction Recognition Time Series Forecasting Recommender Systems Sentiment Analysis NLP(Natural Language Processing) Big Data Visualisation Data Mining Data Scraping Data Analysis Data warehousing Data Modelling So on . . . As I did MSCS (18 years of education in computer science) and Ph.D. student, I can do your project in a smart way. As you can see in my profile, I have been worked for different projects and got a response from employers by getting awesome feedback. Thanks for your response!
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Hi I am a very experienced statistician, data scientist and developer. I have vast experience in data modelling, model building and providing data driven business solutions. I have worked with data from several companies and have done projects involving high level quantitative analysis and data interpretation skills to study the trends, time behaviour and compare the variables in the data. I can do advanced level analysis in SPSS, R, PYTHON, WEKA, TABLEAU and EXCEL tools like machine learning, deep learning, AI, NLP, hypothesis testing, forecasting, T-test, ANOVA etc. Looking forward to discussion, Best Regards, Suyash
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Hello, My total experience is 6.8 years in Predictive modeling Statistical Analysis, Optimization and Machine learning techniques. I have implemented data science solutions for the Digital marketing & advertising, Telecom and Insurance Industries. I am equally comfortable in using a Domain Specific Language like R & Python and statistical tools like SAS, SPSS & EViews. Being excellent in communication, articulate and personable with a talent of relating easily to diverse group of individuals Experience as Data Scientist Interacting with stakeholders throughout the organization to understand the challenges and design business solutions for the same End to end project execution starting from data exploration to insight generation and recommendations Device predictive and descriptive analysis techniques and machine learning algorithms in various projects Coordinate with different functional teams to implement models and monitor outcomes. A drive to learn and master new technologies and techniques. Statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees and text mining, text classification models and Neural Network Querying databases and using statistical computer languages: R, Python and SQL Visualizing/presenting Analysis/Insights/results to business Masters in Statistics –
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frederiksvaerk, Denmark
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