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In this paper, there is description of videos technology has been used widely as well as tried to explore the transform in the structure of selling as well as buying of the product mainly in short videos. With the emergence of the Internet, online procedure are replacing conventional models in our society. Even so, not many recognize the criticality required in E-commerce industry. Video commerce is the next great thing of marketing. It connects to a web page of a dealer selling or giving services rightly from its portal to the consumers. They use a digital shopping cart structure and permit payment by credit card, debit card or electronic fund transfer payments. The E- commerce services helps in decreasing costs in managing orders while also interacting with a broad range of suppliers as well as trading partners. It also requires any type of business transaction in which the parties interconnect electronically rather than by physical exchanges or direct physical contact.

The replacement of traditional shopping fashion by the varied modes of online shopping in real-time. Due to traditional shopping, most of them are becoming into real feel about the merchandise whichever they buy. The merchandise features are going to be manually realized by the consumers whereas in online shopping all the consumers believe the descriptive summary of the products and therefore the various factors supported the sold historical data. Now a day’s modern shopping method is moving gradually towards hitting a greater number of consumers. Here recommendation system playing an important role in suggesting the merchandise by considering the sooner records and increasing the demand. Many of the consumers are attracted by factors like deals on an item, rating, review, and price of the merchandise. Through these factors, most of the consumers are interested in taking online shopping rather than traditional shopping methods. For suggesting the products to consumers, many sorts of recommendation algorithms are applied using machine learning and deep learning technology to coach the system automatically by observing the customer behavior patterns. But the believing factors of the merchandise are going to be forged some time; in such cases, consumers aren't satisfied with their expectations. the general survey of this paper will address the research gap and opportunities with the advice system.

Machine learning-based (IDS) have become a critical component of safeguarding our economic and national security because of the massive quantities of data produced each day and the growing interconnection of the world's Internet infrastructures. The existing machine Learning Model technique may have difficulty comprehending the ever-increasingly complex distribution of data invasion patterns. With a small number of data points, a single deep learning algorithm may be ineffective at capturing different patterns for intrusive attacks. We presented CNN-LSTM Novel Intrusion Detection Model for Big Data to improve the efficiency of IDS-based CNN-LSTM even further (NIDM). NIDM uses behavioural traits and content functions to understand the characteristics when compared to earlier single learning model tactics, this strategy can improve the rate of intrusive attack detection. Keywords: IDS, Machine Learning, LSTM, CNN.